classification parameter estimation and state estimation an engineering approach using matlab



Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB Новинка

Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB

9748.31 руб.
A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods—especially among adaboost varieties and particle filtering methods—have made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including: PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5 Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods All new coverage of the Adaboost and its implementation in PRTools5. A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website.
Edward R. Dougherty Error Estimation for Pattern Recognition Edward R. Dougherty Error Estimation for Pattern Recognition Новинка

Edward R. Dougherty Error Estimation for Pattern Recognition

10123.22 руб.
This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition. Ulisses M. Braga Neto is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, USA. He received his PhD in Electrical and Computer Engineering from The Johns Hopkins University. Dr. Braga Neto received an NSF CAREER Award for his work on error estimation for pattern recognition with applications in genomic signal processing. He is an IEEE Senior Member. Edward R. Dougherty is a Distinguished Professor, Robert F. Kennedy ’26 Chair, and Scientific Director at the Center for Bioinformatics and Genomic Systems Engineering at Texas A&M University, USA. He is a fellow of both the IEEE and SPIE, and he has received the SPIE Presidents Award. Dr. Dougherty has authored several books including Epistemology of the Cell: A Systems Perspective on Biological Knowledge and Random Processes for Image and Signal Processing (Wiley-IEEE Press).
Hebertt Sira-Ramirez Algebraic Identification and Estimation Methods in Feedback Control Systems Hebertt Sira-Ramirez Algebraic Identification and Estimation Methods in Feedback Control Systems Новинка

Hebertt Sira-Ramirez Algebraic Identification and Estimation Methods in Feedback Control Systems

14249.08 руб.
Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws. This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology. Key features: Presents a radically new approach to online parameter and state estimation. Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory. Includes examples in a variety of physical applications with experimental results. Covers the latest developments and applications. Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.
Gregory Mislick K. Cost Estimation. Methods and Tools Gregory Mislick K. Cost Estimation. Methods and Tools Новинка

Gregory Mislick K. Cost Estimation. Methods and Tools

8622.88 руб.
Presents an accessible approach to the cost estimation tools, concepts, and techniques needed to support analytical and cost decisions Written with an easy-to-understand approach, Cost Estimation: Methods and Tools provides comprehensive coverage of the quantitative techniques needed by professional cost estimators and for those wanting to learn about this vibrant career field. Featuring the underlying mathematical and analytical principles of cost estimation, the book focuses on the tools and methods used to predict the research and development, production, and operating and support costs for successful cost estimation in industrial, business, and manufacturing processes. The book begins with a detailed historical perspective and key terms of the cost estimating field in order to develop the necessary background prior to implementing the presented quantitative methods. The book proceeds to fundamental cost estimation methods utilized in the field of cost estimation, including working with inflation indices, regression analysis, learning curves, analogies, cost factors, and wrap rates. With a step-by-step introduction to the practicality of cost estimation and the available resources for obtaining relevant data, Cost Estimation: Methods and Tools also features: Various cost estimating tools, concepts, and techniques needed to support business decisions Multiple questions at the end of each chapter to help readers obtain a deeper understanding of the discussed methods and techniques An overview of the software used in cost estimation, as well as an introduction to the application of risk and uncertainty analysis A Foreword from Dr. Douglas A. Brook, a professor in the Graduate School of Business and Public Policy at the Naval Postgraduate School, who spent many years working in the Department of Defense acquisition environment Cost Estimation: Methods and Tools is an excellent reference for academics and practitioners in decision science, operations research, operations management, business, and systems and industrial engineering, as well as a useful guide in support of professional cost estimation training and certification courses for practitioners. The book is also appropriate for graduate-level courses in operations research, operations management, engineering economics, and manufacturing and/or production processes.
Kevin Murphy D. Modeling and Estimation of Structural Damage Kevin Murphy D. Modeling and Estimation of Structural Damage Новинка

Kevin Murphy D. Modeling and Estimation of Structural Damage

9014.86 руб.
Modelling and Estimation of Damage in Structures is a comprehensiveguide to solving the type of modelling and estimation problems associated with the physics of structural damage. Provides a model-based approach to damage identification Presents an in-depth treatment of probability theory and random processes Covers both theory and algorithms for implementing maximum likelihood and Bayesian estimation approaches Includes experimental examples of all detection and identification approaches Provides a clear means by which acquired data can be used to make decisions regarding maintenance and usage of a structure
David Scott W. Multivariate Density Estimation. Theory, Practice, and Visualization David Scott W. Multivariate Density Estimation. Theory, Practice, and Visualization Новинка

David Scott W. Multivariate Density Estimation. Theory, Practice, and Visualization

8622.88 руб.
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.
Daniele Martini De Success Probability Estimation with Applications to Clinical Trials Daniele Martini De Success Probability Estimation with Applications to Clinical Trials Новинка

Daniele Martini De Success Probability Estimation with Applications to Clinical Trials

7356.67 руб.
Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment Success Probability Estimation with Applications to Clinical Trials details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests. Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation. Success Probability Estimation with Applications to Clinical Trials: • Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries Features practical solutions for problems that are often encountered in clinical trials Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials Success Probability Estimation with Applications to Clinical Trials is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.
Didier Dumur Zonotopes. From Guaranteed State-estimation to Control Didier Dumur Zonotopes. From Guaranteed State-estimation to Control Новинка

Didier Dumur Zonotopes. From Guaranteed State-estimation to Control

6823.75 руб.
This title focuses on two significant problems in the field of automatic control, in particular state estimation and robust Model Predictive Control under input and state constraints, bounded disturbances and measurement noises. The authors build upon previous results concerning zonotopic set-membership state estimation and output feedback tube-based Model Predictive Control. Various existing zonotopic set-membership estimation methods are investigated and their advantages and drawbacks are discussed, making this book suitable both for researchers working in automatic control and industrial partners interested in applying the proposed techniques to real systems. The authors proceed to focus on a new method based on the minimization of the P-radius of a zonotope, in order to obtain a good trade-off between the complexity and the accuracy of the estimation. They propose a P-radius based set-membership estimation method to compute a zonotope containing the real states of a system, which are consistent with the disturbances and measurement noise. The problem of output feedback control using a zonotopic set-membership estimation is also explored. Among the approaches from existing literature on the subject, the implementation of robust predictive techniques based on tubes of trajectories is developed. Contents 1. Uncertainty Representation Based on Set Theory. 2. Several Approaches on Zonotopic Guaranteed Set-Membership Estimation. 3. Zonotopic Guaranteed State Estimation Based on P-Radius Minimization. 4. Tube Model Predictive Control Based on Zonotopic Set-Membership Estimation. About the Authors Vu Tuan Hieu Le is a Research Engineer at the IRSEEM/ESIGELEC Technopôle du Madrillet, Saint Etienne du Rouvray, France. Cristina Stoica is Assistant Professor in the Automatic Control Department at SUPELEC Systems Sciences (E3S), France. Teodoro Alamo is Professor in the Department of Systems Engineering and Automatic Control at the University of Seville, Spain. Eduardo F. Camacho is Professor in the Department of Systems Engineering and Automatic Control at the University of Seville, Spain. Didier Dumur is Professor in the Automatic Control Department, SUPELEC Systems Sciences (E3S), France.
Gebremichael Mekonnen Rainfall. State of the Science Gebremichael Mekonnen Rainfall. State of the Science Новинка

Gebremichael Mekonnen Rainfall. State of the Science

11035.01 руб.
Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 191. Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.
Alireza Javaheri Inside Volatility Filtering. Secrets of the Skew Alireza Javaheri Inside Volatility Filtering. Secrets of the Skew Новинка

Alireza Javaheri Inside Volatility Filtering. Secrets of the Skew

6705.3 руб.
A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of «filtering», this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate data Integrate past observation with Bayesian probability Exploit posterior distribution of the hidden state for optimal estimation Boost trade profitability by utilizing «skewness» opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.
Brenton Clarke R. Robustness Theory and Application Brenton Clarke R. Robustness Theory and Application Новинка

Brenton Clarke R. Robustness Theory and Application

6322.14 руб.
A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop data analytical methods, which are resistant to outlying observations in the data, while capable of detecting outliers, robust statistics is extremely useful for solving an array of common problems, such as estimating location, scale, and regression parameters. Written by an internationally recognized expert in the field of robust statistics, this book addresses a range of well-established techniques while exploring, in depth, new and exciting methodologies. Local robustness and global robustness are discussed, and problems of non-identifiability and adaptive estimation are considered. Rather than attempt an exhaustive investigation of robustness, the author provides readers with a timely review of many of the most important problems in statistical inference involving robust estimation, along with a brief look at confidence intervals for location. Throughout, the author meticulously links research in maximum likelihood estimation with the more general M-estimation methodology. Specific applications and R and some MATLAB subroutines with accompanying data sets—available both in the text and online—are employed wherever appropriate. Providing invaluable insights and guidance, Robustness Theory and Application: Offers a balanced presentation of theory and applications within each topic-specific discussion Features solved examples throughout which help clarify complex and/or difficult concepts Meticulously links research in maximum likelihood type estimation with the more general M-estimation methodology Delves into new methodologies which have been developed over the past decade without stinting on coverage of “tried-and-true” methodologies Includes R and some MATLAB subroutines with accompanying data sets, which help illustrate the power of the methods described Robustness Theory and Application is an important resource for all statisticians interested in the topic of robust statistics. This book encompasses both past and present research, making it a valuable supplemental text for graduate-level courses in robustness.
Biao Huang Dynamic Modeling and Predictive Control in Solid Oxide Fuel Cells. First Principle and Data-based Approaches Biao Huang Dynamic Modeling and Predictive Control in Solid Oxide Fuel Cells. First Principle and Data-based Approaches Новинка

Biao Huang Dynamic Modeling and Predictive Control in Solid Oxide Fuel Cells. First Principle and Data-based Approaches

11993.49 руб.
The high temperature solid oxide fuel cell (SOFC) is identified as one of the leading fuel cell technology contenders to capture the energy market in years to come. However, in order to operate as an efficient energy generating system, the SOFC requires an appropriate control system which in turn requires a detailed modelling of process dynamics. Introducting state-of-the-art dynamic modelling, estimation, and control of SOFC systems, this book presents original modelling methods and brand new results as developed by the authors. With comprehensive coverage and bringing together many aspects of SOFC technology, it considers dynamic modelling through first-principles and data-based approaches, and considers all aspects of control, including modelling, system identification, state estimation, conventional and advanced control. Key features: Discusses both planar and tubular SOFC, and detailed and simplified dynamic modelling for SOFC Systematically describes single model and distributed models from cell level to system level Provides parameters for all models developed for easy reference and reproducing of the results All theories are illustrated through vivid fuel cell application examples, such as state-of-the-art unscented Kalman filter, model predictive control, and system identification techniques to SOFC systems The tutorial approach makes it perfect for learning the fundamentals of chemical engineering, system identification, state estimation and process control. It is suitable for graduate students in chemical, mechanical, power, and electrical engineering, especially those in process control, process systems engineering, control systems, or fuel cells. It will also aid researchers who need a reminder of the basics as well as an overview of current techniques in the dynamic modelling and control of SOFC.
John Ogundare Olusegun Understanding Least Squares Estimation and Geomatics Data Analysis John Ogundare Olusegun Understanding Least Squares Estimation and Geomatics Data Analysis Новинка

John Ogundare Olusegun Understanding Least Squares Estimation and Geomatics Data Analysis

11494.8 руб.
Provides a modern approach to least squares estimation and data analysis for undergraduate land surveying and geomatics programs Rich in theory and concepts, this comprehensive book on least square estimation and data analysis provides examples that are designed to help students extend their knowledge to solving more practical problems. The sample problems are accompanied by suggested solutions, and are challenging, yet easy enough to manually work through using simple computing devices, and chapter objectives provide an overview of the material contained in each section. Understanding Least Squares Estimation and Geomatics Data Analysis begins with an explanation of survey observables, observations, and their stochastic properties. It reviews matrix structure and construction and explains the needs for adjustment. Next, it discusses analysis and error propagation of survey observations, including the application of heuristic rule for covariance propagation. Then, the important elements of statistical distributions commonly used in geomatics are discussed. Main topics of the book include: concepts of datum definitions; the formulation and linearization of parametric, conditional and general model equations involving typical geomatics observables; geomatics problems; least squares adjustments of parametric, conditional and general models; confidence region estimation; problems of network design and pre-analysis; three-dimensional geodetic network adjustment; nuisance parameter elimination and the sequential least squares adjustment; post-adjustment data analysis and reliability; the problems of datum; mathematical filtering and prediction; an introduction to least squares collocation and the kriging methods; and more. Contains ample concepts/theory and content, as well as practical and workable examples Based on the author's manual, which he developed as a complete and comprehensive book for his Adjustment of Surveying Measurements and Special Topics in Adjustments courses Provides geomatics undergraduates and geomatics professionals with required foundational knowledge An excellent companion to Precision Surveying: The Principles and Geomatics Practice Understanding Least Squares Estimation and Geomatics Data Analysis is recommended for undergraduates studying geomatics, and will benefit many readers from a variety of geomatics backgrounds, including practicing surveyors/engineers who are interested in least squares estimation and data analysis, geomatics researchers, and software developers for geomatics.
Mohsen Pourahmadi High-Dimensional Covariance Estimation. With High-Dimensional Data Mohsen Pourahmadi High-Dimensional Covariance Estimation. With High-Dimensional Data Новинка

Mohsen Pourahmadi High-Dimensional Covariance Estimation. With High-Dimensional Data

7195.1 руб.
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.
Tulay Adali Blind Identification and Separation of Complex-valued Signals Tulay Adali Blind Identification and Separation of Complex-valued Signals Новинка

Tulay Adali Blind Identification and Separation of Complex-valued Signals

4423.49 руб.
Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.
Huaping Liu Problem-Based Learning in Communication Systems Using MATLAB and Simulink Huaping Liu Problem-Based Learning in Communication Systems Using MATLAB and Simulink Новинка

Huaping Liu Problem-Based Learning in Communication Systems Using MATLAB and Simulink

9372.7 руб.
Designed to help teach and understand communication systems using a classroom-tested, active learning approach. Discusses communication concepts and algorithms, which are explained using simulation projects, accompanied by MATLAB and Simulink Provides step-by-step code exercises and instructions to implement execution sequences Includes a companion website that has MATLAB and Simulink model samples and templates
Molina Isabel Small Area Estimation Molina Isabel Small Area Estimation Новинка

Molina Isabel Small Area Estimation

8429.52 руб.
Praise for the First Edition «This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic…I believe that it has the potential to turn small area estimation…into a larger area of importance to both researchers and practitioners.» —Journal of the American Statistical Association Written by two experts in the field, Small Area Estimation, Second Edition provides a comprehensive and up-to-date account of the methods and theory of small area estimation (SAE), particularly indirect estimation based on explicit small area linking models. The model-based approach to small area estimation offers several advantages including increased precision, the derivation of «optimal» estimates and associated measures of variability under an assumed model, and the validation of models from the sample data. Emphasizing real data throughout, the Second Edition maintains a self-contained account of crucial theoretical and methodological developments in the field of SAE. The new edition provides extensive accounts of new and updated research, which often involves complex theory to handle model misspecifications and other complexities. Including information on survey design issues and traditional methods employing indirect estimates based on implicit linking models, Small Area Estimation, Second Edition also features: Additional sections describing the use of R code data sets for readers to use when replicating applications Numerous examples of SAE applications throughout each chapter, including recent applications in U.S. Federal programs New topical coverage on extended design issues, synthetic estimation, further refinements and solutions to the Fay-Herriot area level model, basic unit level models, and spatial and time series models A discussion of the advantages and limitations of various SAE methods for model selection from data as well as comparisons of estimates derived from models to reliable values obtained from external sources, such as previous census or administrative data Small Area Estimation, Second Edition is an excellent reference for practicing statisticians and survey methodologists as well as practitioners interested in learning SAE methods. The Second Edition is also an ideal textbook for graduate-level courses in SAE and reliable small area statistics.
Prithwiraj Purkait Transformer Ageing. Monitoring and Estimation Techniques Prithwiraj Purkait Transformer Ageing. Monitoring and Estimation Techniques Новинка

Prithwiraj Purkait Transformer Ageing. Monitoring and Estimation Techniques

11997.76 руб.
A one-stop guide to transformer ageing, presenting industrially relevant state-of-the-art diagnostic techniques backed by extensive research data Offers a comprehensive coverage of transformer ageing topics including insulation materials, condition monitoring and diagnostic techniques Features chapters on smart transformer monitoring frameworks, transformer life estimation and biodegradable oil Highlights industrially relevant techniques adopted in electricity utilities, backed by extensive research
Michael Chernick R. An Introduction to Bootstrap Methods with Applications to R Michael Chernick R. An Introduction to Bootstrap Methods with Applications to R Новинка

Michael Chernick R. An Introduction to Bootstrap Methods with Applications to R

8848.39 руб.
A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.
John Nash C. Nonlinear Parameter Optimization Using R Tools John Nash C. Nonlinear Parameter Optimization Using R Tools Новинка

John Nash C. Nonlinear Parameter Optimization Using R Tools

6223.33 руб.
Nonlinear Parameter Optimization Using R John C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using R In recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non–linear, multivariable conditions, more quickly than ever before. Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: Provides a comprehensive treatment of optimization techniques Examines optimization problems that arise in statistics and how to solve them using R Enables researchers and practitioners to solve parameter determination problems Presents traditional methods as well as recent developments in R Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.
Steven Heston L. The Heston Model and its Extensions in Matlab and C# Steven Heston L. The Heston Model and its Extensions in Matlab and C# Новинка

Steven Heston L. The Heston Model and its Extensions in Matlab and C#

8621.1 руб.
Tap into the power of the most popular stochastic volatility model for pricing equity derivatives Since its introduction in 1993, the Heston model has become a popular model for pricing equity derivatives, and the most popular stochastic volatility model in financial engineering. This vital resource provides a thorough derivation of the original model, and includes the most important extensions and refinements that have allowed the model to produce option prices that are more accurate and volatility surfaces that better reflect market conditions. The book's material is drawn from research papers and many of the models covered and the computer codes are unavailable from other sources. The book is light on theory and instead highlights the implementation of the models. All of the models found here have been coded in Matlab and C#. This reliable resource offers an understanding of how the original model was derived from Ricatti equations, and shows how to implement implied and local volatility, Fourier methods applied to the model, numerical integration schemes, parameter estimation, simulation schemes, American options, the Heston model with time-dependent parameters, finite difference methods for the Heston PDE, the Greeks, and the double Heston model. A groundbreaking book dedicated to the exploration of the Heston model—a popular model for pricing equity derivatives Includes a companion website, which explores the Heston model and its extensions all coded in Matlab and C# Written by Fabrice Douglas Rouah a quantitative analyst who specializes in financial modeling for derivatives for pricing and risk management Engaging and informative, this is the first book to deal exclusively with the Heston Model and includes code in Matlab and C# for pricing under the model, as well as code for parameter estimation, simulation, finite difference methods, American options, and more.
Brani Vidakovic Engineering Biostatistics. An Introduction using MATLAB and WinBUGS Brani Vidakovic Engineering Biostatistics. An Introduction using MATLAB and WinBUGS Новинка

Brani Vidakovic Engineering Biostatistics. An Introduction using MATLAB and WinBUGS

8997.79 руб.
Provides a one-stop resource for engineers learning biostatistics using MATLAB® and WinBUGS Through its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing bio-oriented engineering fields while implementing software packages that are familiar to engineers. The book is heavily oriented to computation and hands-on approaches so readers understand each step of the programming. Another dimension of this book is in parallel coverage of both Bayesian and frequentist approaches to statistical inference. It avoids taking sides on the classical vs. Bayesian paradigms, and many examples in this book are solved using both methods. The results are then compared and commented upon. Readers have the choice of MATLAB® for classical data analysis and WinBUGS/OpenBUGS for Bayesian data analysis. Every chapter starts with a box highlighting what is covered in that chapter and ends with exercises, a list of software scripts, datasets, and references. Engineering Biostatistics: An Introduction using MATLAB® and WinBUGS also includes: parallel coverage of classical and Bayesian approaches, where appropriate substantial coverage of Bayesian approaches to statistical inference material that has been classroom-tested in an introductory statistics course in bioengineering over several years exercises at the end of each chapter and an accompanying website with full solutions and hints to some exercises, as well as additional materials and examples Engineering Biostatistics: An Introduction using MATLAB® and WinBUGS can serve as a textbook for introductory-to-intermediate applied statistics courses, as well as a useful reference for engineers interested in biostatistical approaches.
Maurice Charbit Digital Signal Processing (DSP) with Python Programming Maurice Charbit Digital Signal Processing (DSP) with Python Programming Новинка

Maurice Charbit Digital Signal Processing (DSP) with Python Programming

8997.79 руб.
The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.
Angus Andrews P. Kalman Filtering. Theory and Practice with MATLAB Angus Andrews P. Kalman Filtering. Theory and Practice with MATLAB Новинка

Angus Andrews P. Kalman Filtering. Theory and Practice with MATLAB

10047.81 руб.
The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Gary Kinzel L. Kinematics, Dynamics, and Design of Machinery Gary Kinzel L. Kinematics, Dynamics, and Design of Machinery Новинка

Gary Kinzel L. Kinematics, Dynamics, and Design of Machinery

9748.31 руб.
Kinematics, Dynamics, and Design of Machinery, Third Edition, presents a fresh approach to kinematic design and analysis and is an ideal textbook for senior undergraduates and graduates in mechanical, automotive and production engineering Presents the traditional approach to the design and analysis of kinematic problems and shows how GCP can be used to solve the same problems more simply Provides a new and simpler approach to cam design Includes an increased number of exercise problems Accompanied by a website hosting a solutions manual, teaching slides and MATLAB® programs
Peter Goos Statistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos Statistics with JMP: Hypothesis Tests, ANOVA and Regression Новинка

Peter Goos Statistics with JMP: Hypothesis Tests, ANOVA and Regression

5634.29 руб.
Statistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos, University of Leuven and University of Antwerp, Belgium David Meintrup, University of Applied Sciences Ingolstadt, Germany A first course on basic statistical methodology using JMP This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software. Key features: Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested. Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values). Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic. Promotes the use of graphs and confidence intervals in addition to p-values. Course materials and tutorials for teaching are available on the book's companion website. Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.
Vincent Savaux MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems Vincent Savaux MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems Новинка

Vincent Savaux MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

5473.51 руб.
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature
Michael Pecht Reliability Engineering Michael Pecht Reliability Engineering Новинка

Michael Pecht Reliability Engineering

10872.33 руб.
An Integrated Approach to Product Development Reliability Engineering presents an integrated approach to the design, engineering, and management of reliability activities throughout the life cycle of a product, including concept, research and development, design, manufacturing, assembly, sales, and service. Containing illustrative guides that include worked problems, numerical examples, homework problems, a solutions manual, and class-tested materials, it demonstrates to product development and manufacturing professionals how to distribute key reliability practices throughout an organization. The authors explain how to integrate reliability methods and techniques in the Six Sigma process and Design for Six Sigma (DFSS). They also discuss relationships between warranty and reliability, as well as legal and liability issues. Other topics covered include: Reliability engineering in the 21st Century Probability life distributions for reliability analysis Process control and process capability Failure modes, mechanisms, and effects analysis Health monitoring and prognostics Reliability tests and reliability estimation Reliability Engineering provides a comprehensive list of references on the topics covered in each chapter. It is an invaluable resource for those interested in gaining fundamental knowledge of the practical aspects of reliability in design, manufacturing, and testing. In addition, it is useful for implementation and management of reliability programs.
Jasveer Singh Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication Jasveer Singh Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication Новинка

Jasveer Singh Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication

8997.79 руб.
Presents a new, effective methodology in software size measurement Software size measurement is an extremely important and highly specialized aspect of the software life cycle. It is used for determining the effort and cost estimations for project planning purposes of a software project’s execution, and/or for other costing, charging, and productivity analysis purposes. Many software projects exceed their allocated budget limits because the methodologies currently available lack accuracy. The new software size measurement methodology presented in this book offers a complete procedure that overcomes the deficiencies of the current methodologies, allowing businesses to estimate the size and required effort correctly for all their software projects developed in high level languages. The Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication (FSSM) allows for projects to be completed within the defined budget limits by obtaining accurate estimations. The methodology provides comprehensive and precise measurements of the complete software whereby factual software size determination, development effort estimation, and performance indications are obtained. The approach is elaborate, effective and accurate for software size measurement and development effort estimation, avoiding inaccurate project planning of software projects. Key features: Pinpoints one of the major, originating root causes of erroneous planning by disclosing hidden errors made in software size measurement, and consequently in effort estimates and project planning All the major relevant and important aspects of software size measurement are taken into consideration and clearly presented to the reader Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication is a vital reference for software professionals and Master level students in software engineering. For further information and materials relating to this book, such as FSSM 1.0 Calculations Template for Results Tables and Graphs, containing Calculations, and Results Tables/Graphs for the Mini FSSM Example, please visit the following two accompanying websites: http://booksupport.wiley.com www.fssm.software
Haitham Abu-Rub Variable Speed AC Drives with Inverter Output Filters Haitham Abu-Rub Variable Speed AC Drives with Inverter Output Filters Новинка

Haitham Abu-Rub Variable Speed AC Drives with Inverter Output Filters

8348.99 руб.
The advance of variable speed drives systems (VSDs) engineering highlights the need of specific technical guidance provision by electrical machines and drives manufacturers, so that such applications can be properly designed to present advantages in terms of both energy efficiency and expenditure. This book presents problems and solutions related to inverter-fed electrical motors. Practically orientated, the book describes the reasons, theory and analysis of those problems. Various solutions for individual problems are presented together with the complete design process, modelling and simulation examples with MATLAB/Simulink on the companion website. A key focus of Variable Speed AC Drives with Inverter Output Filters is to examine the state variables estimation and motor control structures which have to be modified according to the used solution (filter). In most control systems the structure and parameters are taken into account to make it possible for precise control of the motor. This methodology is able to include modifications and extensions depending on specific control and estimation structures. Highly accessible, this is an invaluable resource for practising R&D engineers in drive companies, power electronics & control engineers and manufacturers of electrical drives. Senior undergraduate and postgraduate students in electronics and control engineering will also find it of value.
Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering Новинка

Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering

11622.14 руб.
Provides readers an understanding of the basic physics underlying meta-materials, providing a powerful tool for analyzing their electromagnetic properties Periodic Structures: Mode-Matching Approach and Applications in Electromagnetic Engineering presents the scattering and guiding characteristics of periodic structures using the mode-matching approach and their applications in electromagnetic engineering. The book is structured so that the first three chapters provide an introduction and prepare the reader for chapters 4 to 6, which expand the formulations to electromagnetic and optical structures applicable to practical device applications. The last chapters cover very recent research topics in electromagnetics and optics. Provides an analytic approach to describing the operation of photonic crystals and related periodic structures Covers guided and leaky mode propagation in periodic surroundings, from fundamentals to practical device applications Demostrates formulation of the periodic system and applications to practical electromagnetic / optical devices, even further to metamaterials Introduces the evolution of periodic structures and their applications in microwave, millimeter wave and THz. Written by a high-impact author in electromagnetics and optics Contains mathematical derivations which can be applied directly to MATLAB programs Ideal for Graduate students and advanced undergraduates in electronic engineering, optics, physics, and applied physics, or researchers working with periodic structures
Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering Новинка

Ruey-Bing Hwang (Raybeam) Periodic Structures. Mode-Matching Approach and Applications in Electromagnetic Engineering

11877.96 руб.
Provides readers an understanding of the basic physics underlying meta-materials, providing a powerful tool for analyzing their electromagnetic properties Periodic Structures: Mode-Matching Approach and Applications in Electromagnetic Engineering presents the scattering and guiding characteristics of periodic structures using the mode-matching approach and their applications in electromagnetic engineering. The book is structured so that the first three chapters provide an introduction and prepare the reader for chapters 4 to 6, which expand the formulations to electromagnetic and optical structures applicable to practical device applications. The last chapters cover very recent research topics in electromagnetics and optics. Provides an analytic approach to describing the operation of photonic crystals and related periodic structures Covers guided and leaky mode propagation in periodic surroundings, from fundamentals to practical device applications Demostrates formulation of the periodic system and applications to practical electromagnetic / optical devices, even further to metamaterials Introduces the evolution of periodic structures and their applications in microwave, millimeter wave and THz. Written by a high-impact author in electromagnetics and optics Contains mathematical derivations which can be applied directly to MATLAB programs Ideal for Graduate students and advanced undergraduates in electronic engineering, optics, physics, and applied physics, or researchers working with periodic structures
Paolo Brandimarte Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics Paolo Brandimarte Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics Новинка

Paolo Brandimarte Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics

11877.96 руб.
An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Thomas Taimre Handbook of Monte Carlo Methods Thomas Taimre Handbook of Monte Carlo Methods Новинка

Thomas Taimre Handbook of Monte Carlo Methods

12971.67 руб.
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
Chen YangQuan System Simulation Techniques with MATLAB and Simulink Chen YangQuan System Simulation Techniques with MATLAB and Simulink Новинка

Chen YangQuan System Simulation Techniques with MATLAB and Simulink

9808.9 руб.
System Simulation Techniques with MATLAB and Simulink comprehensively explains how to use MATLAB and Simulink to perform dynamic systems simulation tasks for engineering and non-engineering applications. This book begins with covering the fundamentals of MATLAB programming and applications, and the solutions to different mathematical problems in simulation. The fundamentals of Simulink modelling and simulation are then presented, followed by coverage of intermediate level modelling skills and more advanced techniques in Simulink modelling and applications. Finally the modelling and simulation of engineering and non-engineering systems are presented. The areas covered include electrical, electronic systems, mechanical systems, pharmacokinetic systems, video and image processing systems and discrete event systems. Hardware-in-the-loop simulation and real-time application are also discussed. Key features: Progressive building of simulation skills using Simulink, from basics through to advanced levels, with illustrations and examples Wide coverage of simulation topics of applications from engineering to non-engineering systems Dedicated chapter on hardware-in-the-loop simulation and real time control End of chapter exercises A companion website hosting a solution manual and powerpoint slides System Simulation Techniques with MATLAB and Simulink is a suitable textbook for senior undergraduate/postgraduate courses covering modelling and simulation, and is also an ideal reference for researchers and practitioners in industry.
Xuefeng Yin Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications Xuefeng Yin Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications Новинка

Xuefeng Yin Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications

10497.42 руб.
A comprehensive reference giving a thorough explanation of propagation mechanisms, channel characteristics results, measurement approaches and the modelling of channels Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are then presented, which include conventional spectral-based estimation, the specular-path-model based high-resolution method, and the newly derived power spectrum estimation methods. Measurement results are used to compare the performance of the different estimation methods. The third part gives a complete introduction to different modelling approaches. Among them, both scattering theoretical channel modelling and measurement-based channel modelling approaches are detailed. This part also approaches how to utilize these two modelling approaches to investigate wireless channels for conventional cellular systems and some new emerging communication systems. This three-part approach means the book caters for the requirements of the audiences at different levels, including readers needing introductory knowledge, engineers who are looking for more advanced understanding, and expert researchers in wireless system design as a reference. Presents technical explanations, illustrated with examples of the theory in practice Discusses results applied to 4G communication systems and other emerging communication systems, such as relay, CoMP, and vehicle-to-vehicle rapid time-variant channels Can be used as comprehensive tutorial for students or a complete reference for engineers in industry Includes selected illustrations in color Program downloads available for readers Companion website with program downloads for readers and presentation slides and solution manual for instructors Essential reading for Graduate students and researchers interested in the characteristics of propagation channel, or who work in areas related to physical layer architectures, air interfaces, navigation, and wireless sensing
Monica Pratesi Analysis of Poverty Data by Small Area Estimation Monica Pratesi Analysis of Poverty Data by Small Area Estimation Новинка

Monica Pratesi Analysis of Poverty Data by Small Area Estimation

6658.7 руб.
A comprehensive guide to implementing SAE methods for poverty studies and poverty mapping There is an increasingly urgent demand for poverty and living conditions data, in relation to local areas and/or subpopulations. Policy makers and stakeholders need indicators and maps of poverty and living conditions in order to formulate and implement policies, (re)distribute resources, and measure the effect of local policy actions. Small Area Estimation (SAE) plays a crucial role in producing statistically sound estimates for poverty mapping. This book offers a comprehensive source of information regarding the use of SAE methods adapted to these distinctive features of poverty data derived from surveys and administrative archives. The book covers the definition of poverty indicators, data collection and integration methods, the impact of sampling design, weighting and variance estimation, the issue of SAE modelling and robustness, the spatio-temporal modelling of poverty, and the SAE of the distribution function of income and inequalities. Examples of data analyses and applications are provided, and the book is supported by a website describing scripts written in SAS or R software, which accompany the majority of the presented methods. Key features: Presents a comprehensive review of SAE methods for poverty mapping Demonstrates the applications of SAE methods using real-life case studies Offers guidance on the use of routines and choice of websites from which to download them Analysis of Poverty Data by Small Area Estimation offers an introduction to advanced techniques from both a practical and a methodological perspective, and will prove an invaluable resource for researchers actively engaged in organizing, managing and conducting studies on poverty.
David Hampton Hedge Fund Modelling and Analysis using MATLAB David Hampton Hedge Fund Modelling and Analysis using MATLAB Новинка

David Hampton Hedge Fund Modelling and Analysis using MATLAB

6066.7 руб.
The second book in Darbyshire and Hampton’s Hedge Fund Modelling and Analysis series, Hedge Fund Modelling and Analysis Using MATLAB® takes advantage of the huge library of built-in functions and suite of financial and analytic packages available to MATLAB®. This allows for a more detailed analysis of some of the more computationally intensive and advanced topics, such as hedge fund classification, performance measurement and mean-variance optimisation. Darbyshire and Hampton’s first book in the series, Hedge Fund Modelling and Analysis Using Excel & and VBA, is seen as a valuable supplementary text to this book. Starting with an overview of the hedge fund industry the book then looks at a variety of commercially available hedge fund data sources. After covering key statistical techniques and methods, the book discusses mean-variance optimisation, hedge fund classification and performance with an emphasis on risk-adjusted return metrics. Finally, common hedge fund market risk management techniques, such as traditional Value-at-Risk methods, modified extensions and expected shortfall are covered. The book’s dedicated website, www.darbyshirehampton.com provides free downloads of all the data and MATLAB® source code, as well as other useful resources. Hedge Fund Modelling and Analysis Using MATLAB® serves as a definitive introductory guide to hedge fund modelling and analysis and will provide investors, industry practitioners and students alike with a useful range of tools and techniques for analysing and estimating alpha and beta sources of return, performing manager ranking and market risk management.
Mohammad Arashi Theory of Ridge Regression Estimation with Applications Mohammad Arashi Theory of Ridge Regression Estimation with Applications Новинка

Mohammad Arashi Theory of Ridge Regression Estimation with Applications

11954.59 руб.
A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators.The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Bertram K. C. Chan Applied Probabilistic Calculus for Financial Engineering. An Introduction Using R Bertram K. C. Chan Applied Probabilistic Calculus for Financial Engineering. An Introduction Using R Новинка

Bertram K. C. Chan Applied Probabilistic Calculus for Financial Engineering. An Introduction Using R

10123.22 руб.
Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a «Random Walk» Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.
Steven Thompson K. Sampling Steven Thompson K. Sampling Новинка

Steven Thompson K. Sampling

10115.42 руб.
Praise for the Second Edition «This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book.» —Technometrics «Well-written . . . an excellent book on an important subject. Highly recommended.» —Choice «An ideal reference for scientific researchers and other professionals who use sampling.» —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more. Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.
Moustapha Doumiati Vehicle Dynamics Estimation using Kalman Filtering. Experimental Validation Moustapha Doumiati Vehicle Dynamics Estimation using Kalman Filtering. Experimental Validation Новинка

Moustapha Doumiati Vehicle Dynamics Estimation using Kalman Filtering. Experimental Validation

10422.72 руб.
Vehicle dynamics and stability have been of considerable interest for a number of years. The obvious dilemma is that people naturally desire to drive faster and faster yet expect their vehicles to be “infinitely” stable and safe during all normal and emergency maneuvers. For the most part, people pay little attention to the limited handling potential of their vehicles until some unusual behavior is observed that often results in accidents and even fatalities. This book presents several model-based estimation methods which involve information from current potential-integrable sensors. Improving vehicle control and stabilization is possible when vehicle dynamic variables are known. The fundamental problem is that some essential variables related to tire/road friction are difficult to measure because of technical and economical reasons. Therefore, these data must be estimated. It is against this background, that this book’s objective is to develop estimators in order to estimate the vehicle’s load transfer, the sideslip angle, and the vertical and lateral tire/road forces using a roll model. The proposed estimation processes are based on the state observer (Kalman filtering) theory and the dynamic response of a vehicle instrumented with standard sensors. These estimators are able to work in real time in normal and critical driving situations. Performances are tested using an experimental car in real driving situations. This is exactly the focus of this book, providing students, technicians and engineers from the automobile field with a theoretical basis and some practical algorithms useful for estimating vehicle dynamics in real-time during vehicle motion.
Stephen Westland Computational Colour Science Using MATLAB Stephen Westland Computational Colour Science Using MATLAB Новинка

Stephen Westland Computational Colour Science Using MATLAB

9298 руб.
Computational Colour Science Using MATLAB 2nd Edition offers a practical, problem-based approach to colour physics. The book focuses on the key issues encountered in modern colour engineering, including efficient representation of colour information, Fourier analysis of reflectance spectra and advanced colorimetric computation. Emphasis is placed on the practical applications rather than the techniques themselves, with material structured around key topics. These topics include colour calibration of visual displays, computer recipe prediction and models for colour-appearance prediction. Each topic is carefully introduced at three levels to aid student understanding. First, theoretical ideas and background information are discussed, then explanations of mathematical solutions follow and finally practical solutions are presented using MATLAB. The content includes: A compendium of equations and numerical data required by the modern colour and imaging scientist. Numerous examples of solutions and algorithms for a wide-range of computational problems in colour science. Example scripts using the MATLAB programming language. This 2nd edition contains substantial new and revised material, including three innovative chapters on colour imaging, psychophysical methods, and physiological colour spaces; the MATLAB toolbox has been extended with a professional, optimized, toolbox to go alongside the current teaching toolbox; and a java toolbox has been added which will interest users who are writing web applications and/or applets or mobile phone applications. Computational Colour Science Using MATLAB 2nd Edition is an invaluable resource for students taking courses in colour science, colour chemistry and colour physics as well as technicians and researchers working in the area. In addition, it acts a useful reference for professionals and researchers working in colour dependent industries such as textiles, paints, print & electronic imaging. Review from First Edition: “…highly recommended as a concise introduction to the practicalities of colour science…” (Color Technology, 2004)
Sucharita Ghosh Kernel Smoothing. Principles, Methods and Applications Sucharita Ghosh Kernel Smoothing. Principles, Methods and Applications Новинка

Sucharita Ghosh Kernel Smoothing. Principles, Methods and Applications

6748.34 руб.
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of contexts, considering independent and correlated data e.g. with short-memory and long-memory correlations, as well as non-Gaussian data that are transformations of latent Gaussian processes. These types of data occur in many fields of research, e.g. the natural and the environmental sciences, and others. Nonparametric density estimation, nonparametric and semiparametric regression, trend and surface estimation in particular for time series and spatial data and other topics such as rapid change points, robustness etc. are introduced alongside a study of their theoretical properties and optimality issues, such as consistency and bandwidth selection. Addressing a variety of topics, Kernel Smoothing: Principles, Methods and Applications offers a user-friendly presentation of the mathematical content so that the reader can directly implement the formulas using any appropriate software. The overall aim of the book is to describe the methods and their theoretical backgrounds, while maintaining an analytically simple approach and including motivating examples—making it extremely useful in many sciences such as geophysics, climate research, forestry, ecology, and other natural and life sciences, as well as in finance, sociology, and engineering. A simple and analytical description of kernel smoothing methods in various contexts Presents the basics as well as new developments Includes simulated and real data examples Kernel Smoothing: Principles, Methods and Applications is a textbook for senior undergraduate and graduate students in statistics, as well as a reference book for applied statisticians and advanced researchers.
Issouf Soumare Stochastic Simulation and Applications in Finance with MATLAB Programs Issouf Soumare Stochastic Simulation and Applications in Finance with MATLAB Programs Новинка

Issouf Soumare Stochastic Simulation and Applications in Finance with MATLAB Programs

10123.22 руб.
Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.
Harry Trees L.Van Detection Estimation and Modulation Theory, Part I. Detection, Estimation, and Filtering Theory Harry Trees L.Van Detection Estimation and Modulation Theory, Part I. Detection, Estimation, and Filtering Theory Новинка

Harry Trees L.Van Detection Estimation and Modulation Theory, Part I. Detection, Estimation, and Filtering Theory

8548.18 руб.
Originally published in 1968, Harry Van Trees’s Detection, Estimation, and Modulation Theory, Part I is one of the great time-tested classics in the field of signal processing. Highly readable and practically organized, it is as imperative today for professionals, researchers, and students in optimum signal processing as it was over thirty years ago. The second edition is a thorough revision and expansion almost doubling the size of the first edition and accounting for the new developments thus making it again the most comprehensive and up-to-date treatment of the subject. With a wide range of applications such as radar, sonar, communications, seismology, biomedical engineering, and radar astronomy, among others, the important field of detection and estimation has rarely been given such expert treatment as it is here. Each chapter includes section summaries, realistic examples, and a large number of challenging problems that provide excellent study material. This volume which is Part I of a set of four volumes is the most important and widely used textbook and professional reference in the field.
Oge Marques Practical Image and Video Processing Using MATLAB Oge Marques Practical Image and Video Processing Using MATLAB Новинка

Oge Marques Practical Image and Video Processing Using MATLAB

13100.24 руб.
Up-to-date, technically accurate coverage of essential topics in image and video processing This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation. The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own. Supplemental resources for readers and instructors can be found at http://www.ogemarques.com
Alexander Kniazev Introduction to Bayesian Estimation and Copula Models of Dependence Alexander Kniazev Introduction to Bayesian Estimation and Copula Models of Dependence Новинка

Alexander Kniazev Introduction to Bayesian Estimation and Copula Models of Dependence

8622.88 руб.
Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.
Ming Xiao Geotechnical Engineering Design Ming Xiao Geotechnical Engineering Design Новинка

Ming Xiao Geotechnical Engineering Design

4097.66 руб.
An accessible, clear, concise, and contemporary course in geotechnical engineering design. covers the major in geotechnical engineering packed with self-test problems and projects with an on-line detailed solutions manual presents the state-of-the-art field practice covers both Eurocode 7 and ASTM standards (for the US)
Subchan Dr Subchan Computational Optimal Control. Tools and Practice Subchan Dr Subchan Computational Optimal Control. Tools and Practice Новинка

Subchan Dr Subchan Computational Optimal Control. Tools and Practice

13027.44 руб.
Computational Optimal Control: Tools and Practice provides a detailed guide to informed use of computational optimal control in advanced engineering practice, addressing the need for a better understanding of the practical application of optimal control using computational techniques. Throughout the text the authors employ an advanced aeronautical case study to provide a practical, real-life setting for optimal control theory. This case study focuses on an advanced, real-world problem known as the “terminal bunt manoeuvre” or special trajectory shaping of a cruise missile. Representing the many problems involved in flight dynamics, practical control and flight path constraints, this case study offers an excellent illustration of advanced engineering practice using optimal solutions. The book describes in practical detail the real and tested optimal control software, examining the advantages and limitations of the technology. Featuring tutorial insights into computational optimal formulations and an advanced case-study approach to the topic, Computational Optimal Control: Tools and Practice provides an essential handbook for practising engineers and academics interested in practical optimal solutions in engineering. Focuses on an advanced, real-world aeronautical case study examining optimisation of the bunt manoeuvre Covers DIRCOL, NUDOCCCS, PROMIS and SOCS (under the GESOP environment), and BNDSCO Explains how to configure and optimize software to solve complex real-world computational optimal control problems Presents a tutorial three-stage hybrid approach to solving optimal control problem formulations
John Shynk J. Probability, Random Variables, and Random Processes. Theory and Signal Processing Applications John Shynk J. Probability, Random Variables, and Random Processes. Theory and Signal Processing Applications Новинка

John Shynk J. Probability, Random Variables, and Random Processes. Theory and Signal Processing Applications

11111.64 руб.
Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several appendices include related material on integration, important inequalities and identities, frequency-domain transforms, and linear algebra. These topics have been included so that the book is relatively self-contained. One appendix contains an extensive summary of 33 random variables and their properties such as moments, characteristic functions, and entropy. Unlike most books on probability, numerous figures have been included to clarify and expand upon important points. Over 600 illustrations and MATLAB plots have been designed to reinforce the material and illustrate the various characterizations and properties of random quantities. Sufficient statistics are covered in detail, as is their connection to parameter estimation techniques. These include classical Bayesian estimation and several optimality criteria: mean-square error, mean-absolute error, maximum likelihood, method of moments, and least squares. The last four chapters provide an introduction to several topics usually studied in subsequent engineering courses: communication systems and information theory; optimal filtering (Wiener and Kalman); adaptive filtering (FIR and IIR); and antenna beamforming, channel equalization, and direction finding. This material is available electronically at the companion website. Probability, Random Variables, and Random Processes is the only textbook on probability for engineers that includes relevant background material, provides extensive summaries of key results, and extends various statistical techniques to a range of applications in signal processing.
Arora Ravindra High Voltage and Electrical Insulation Engineering Arora Ravindra High Voltage and Electrical Insulation Engineering Новинка

Arora Ravindra High Voltage and Electrical Insulation Engineering

8885.48 руб.
The book is written for students as well as for teachers and researchers in the field of High Voltage and Insulation Engineering. It is based on the advance level courses conducted at TU Dresden, Germany and Indian Institute of Technology Kanpur, India. The book has a novel approach describing the fundamental concept of field dependent behavior of dielectrics subjected to high voltage. There is no other book in the field of high voltage engineering following this new approach in describing the behavior of dielectrics. The contents begin with the description of fundamental terminology in the subject of high voltage engineering. It is followed by the classification of electric fields and the techniques of field estimation. Performance of gaseous, liquid and solid dielectrics under different field conditions is described in the subsequent chapters. Separate chapters on vacuum as insulation and the lightning phenomenon are included.
Sue Black Age Estimation in the Living. The Practitioner's Guide Sue Black Age Estimation in the Living. The Practitioner's Guide Новинка

Sue Black Age Estimation in the Living. The Practitioner's Guide

12368.4 руб.
This book summarizes and explains the main approaches to age estimation in the living, defining when a parameter may be of use and raising awareness of its limitations. This text ensures that practitioners recognize when an assessment is beyond their area of expertise or beyond verification depending upon the clinical data available. Each key approach to age evaluation has been allotted a single chapter, written by an international leader in the particular field. The book also includes summary chapters that relay readily accessible data for use by the practitioner, and includes important “ageing milestones.” This book is indispensable where problems of immigration and legal standing, juvenile vs. adult criminal status, and responsibilities of law enforcement to protect vulnerable persons are key issues on a daily basis. Medical practitioners, forensic practitioners such as pathology, odontology, anthropology and nursing, lawyers, and police would find this book incredibly useful.
Jianjun Gao Heterojunction Bipolar Transistors for Circuit Design. Microwave Modeling and Parameter Extraction Jianjun Gao Heterojunction Bipolar Transistors for Circuit Design. Microwave Modeling and Parameter Extraction Новинка

Jianjun Gao Heterojunction Bipolar Transistors for Circuit Design. Microwave Modeling and Parameter Extraction

10497.42 руб.
A highly comprehensive summary on circuit related modeling techniques and parameter extraction methods for heterojunction bipolar transistors • Heterojunction Bipolar Transistor (HBT) is one of the most important devices for microwave applications. The book details the accurate device modeling for HBTs and high level IC design using HBTs • Provides a valuable reference to basic modeling issues and specific semiconductor device models encountered in circuit simulators, with a thorough reference list at the end of each chapter for onward learning • Offers an overview on modeling techniques and parameter extraction methods for heterojunction bipolar transistors focusing on circuit simulation and design • Presents electrical/RF engineering-related theory and tools and include equivalent circuits and their matrix descriptions, noise, small and large signal analysis methods
Bethlehem Jelke Handbook of Web Surveys Bethlehem Jelke Handbook of Web Surveys Новинка

Bethlehem Jelke Handbook of Web Surveys

13104.07 руб.
BEST PRACTICES TO CREATE AND IMPLEMENTHIGHLY EFFECTIVE WEB SURVEYS Exclusively combining design and sampling issues, Handbook of Web Surveys presents a theoretical yet practical approach to creating and conducting web surveys. From the history of web surveys to various modes of data collection to tips for detecting error, this book thoroughly introduces readers to the this cutting-edge technique and offers tips for creating successful web surveys. The authors provide a history of web surveys and go on to explore the advantages and disadvantages of this mode of data collection. Common challenges involving under-coverage, self-selection, and measurement errors are discussed as well as topics including: Sampling designs and estimation procedures Comparing web surveys to face-to-face, telephone, and mail surveys Errors in web surveys Mixed-mode surveys Weighting techniques including post-stratification, generalized regression estimation, and raking ratio estimation Use of propensity scores to correct bias Web panels Real-world examples illustrate the discussed concepts, methods, and techniques, with related data freely available on the book's Website. Handbook of Web Surveys is an essential reference for researchers in the fields of government, business, economics, and the social sciences who utilize technology to gather, analyze, and draw results from data. It is also a suitable supplement for survey methods courses at the upper-undergraduate and graduate levels.
Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach Новинка

Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach

4609.87 руб.
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.
Elsayed Elsayed A. Reliability Engineering Elsayed Elsayed A. Reliability Engineering Новинка

Elsayed Elsayed A. Reliability Engineering

12640.45 руб.
A newly revised and updated edition that details both the theoretical foundations and practical applications of reliability engineering Reliability is one of the most important quality characteristics of components, products, and large and complex systems—but it takes a significant amount of time and resources to bring reliability to fruition. Thoroughly classroom- and industry-tested, this book helps ensure that engineers see reliability success with every product they design, test, and manufacture. Divided into three parts, Reliability Engineering, Second Edition handily describes the theories and their practical uses while presenting readers with real-world examples and problems to solve. Part I focuses on system reliability estimation for time independent and failure dependent models, helping engineers create a reliable design. Part II aids the reader in assembling necessary components and configuring them to achieve desired reliability objectives, conducting reliability tests on components, and using field data from similar components. Part III follows what happens once a product is produced and sold, how the manufacturer must ensure its reliability objectives by providing preventive and scheduled maintenance and warranty policies. This Second Edition includes in-depth and enhanced chapter coverage of: Reliability and Hazard Functions System Reliability Evaluation Time- and Failure-Dependent Reliability Estimation Methods of the Parameters of Failure-Time Distributions Parametric Reliability Models Models for Accelerated Life Testing Renewal Processes and Expected Number of Failures Preventive Maintenance and Inspection Warranty Models Case Studies A comprehensive reference for practitioners and professionals in quality and reliability engineering, Reliability Engineering can also be used for senior undergraduate or graduate courses in industrial and systems, mechanical, and electrical engineering programs.
Rune Brincker Introduction to Operational Modal Analysis Rune Brincker Introduction to Operational Modal Analysis Новинка

Rune Brincker Introduction to Operational Modal Analysis

8963.64 руб.
Comprehensively covers the basic principles and practice of Operational Modal Analysis (OMA). Covers all important aspects that are needed to understand why OMA is a practical tool for modal testing Covers advanced topics, including closely spaced modes, mode shape scaling, mode shape expansion and estimation of stress and strain in operational responses Discusses practical applications of Operational Modal Analysis Includes examples supported by MATLAB® applications Accompanied by a website hosting a MATLAB® toolbox for Operational Modal Analysis
Alexander Papusha N. Beam Theory for Subsea Pipelines. Analysis and Practical Applications Alexander Papusha N. Beam Theory for Subsea Pipelines. Analysis and Practical Applications Новинка

Alexander Papusha N. Beam Theory for Subsea Pipelines. Analysis and Practical Applications

14622.12 руб.
Introducing a new practical approach within the field of applied mechanics developed to solve beam strength and bending problems using classical beam theory and beam modeling, this outstanding new volume offers the engineer, scientist, or student a revolutionary new approach to subsea pipeline design. Integrating use of the Mathematica program into these models and designs, the engineer can utilize this unique approach to build stronger, more efficient and less costly subsea pipelines, a very important phase of the world's energy infrastructure. Significant advances have been achieved in implementation of the applied beam theory in various engineering design technologies over the last few decades, and the implementation of this theory also takes an important place within the practical area of re-qualification and reassessment for onshore and offshore pipeline engineering. A general strategy of applying beam theory into the design procedure of subsea pipelines has been developed and already incorporated into the ISO guidelines for reliability-based limit state design of pipelines. This work is founded on these significant advances. The intention of the book is to provide the theory, research, and practical applications that can be used for educational purposes by personnel working in offshore pipeline integrity and engineering students. A must-have for the veteran engineer and student alike, this volume is an important new advancement in the energy industry, a strong link in the chain of the world's energy production.
Mohamed Ben-Daya Introduction to Maintenance Engineering. Modelling, Optimization and Management Mohamed Ben-Daya Introduction to Maintenance Engineering. Modelling, Optimization and Management Новинка

Mohamed Ben-Daya Introduction to Maintenance Engineering. Modelling, Optimization and Management

6402.6 руб.
This introductory textbook links theory with practice using real illustrative cases involving products, plants and infrastructures and exposes the student to the evolutionary trends in maintenance. Provides an interdisciplinary approach which links, engineering, science, technology, mathematical modelling, data collection and analysis, economics and management Blends theory with practice illustrated through examples relating to products, plants and infrastructures Focuses on concepts, tools and techniques Identifies the special management requirements of various engineered objects (products, plants, and infrastructures)

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Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.
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