bayesian signal processing classical modern and particle filtering methods



James Candy V. Bayesian Signal Processing. Classical, Modern, and Particle Filtering Methods James Candy V. Bayesian Signal Processing. Classical, Modern, and Particle Filtering Methods Новинка

James Candy V. Bayesian Signal Processing. Classical, Modern, and Particle Filtering Methods

10497.42 руб.
Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.
François Auger Signal Processing with Free Software. Practical Experiments François Auger Signal Processing with Free Software. Practical Experiments Новинка

François Auger Signal Processing with Free Software. Practical Experiments

4827.82 руб.
An ideal resource for students, industrial engineers, and researchers, Signal Processing with Free Software Practical Experiments presents practical experiments in signal processing using free software. The text introduces elementary signals through elementary waveform, signal storage files and elementary operations on signals and then presents the first tools to signal analysis such as temporal and frequency characteristics leading to Time-frequency analysis. Non-parametric spectral analysis is also discussed as well as signal processing through sampling, resampling, quantification, and analog and digital filtering. Table of Contents: 1. Generation of Elementary Signals. Generation of Elementary Waveform. – Elementary Operations on the Signals. – Format of Signal Storage Files. 2. First tools of Signal Analysis. Measurement of Temporal and Frequency Characteristics of a Signal. Time-Frequency Analysis of a Signal. 3. Non-parametric Spectral Analysis. 4. Signal Processing. Sampling. – Resampling. – Quantification. – “Analog” Filtering. Digital Filtering
Saeed Vaseghi V. Advanced Digital Signal Processing and Noise Reduction Saeed Vaseghi V. Advanced Digital Signal Processing and Noise Reduction Новинка

Saeed Vaseghi V. Advanced Digital Signal Processing and Noise Reduction

12261.12 руб.
Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Two new chapters on MIMO systems, correlation and Eigen analysis and independent component analysis Comprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information processing systems Examples and applications in signal and information extraction from noisy data Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction models Advanced Digital Signal Processing and Noise Reduction is an invaluable text for postgraduates, senior undergraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be of interest to professional engineers in telecommunications and audio and signal processing industries and network planners and implementers in mobile and wireless communication communities.
Adali Tülay Adaptive Signal Processing. Next Generation Solutions Adali Tülay Adaptive Signal Processing. Next Generation Solutions Новинка

Adali Tülay Adaptive Signal Processing. Next Generation Solutions

11877.96 руб.
Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cutting edge of its own area of specialty. It begins by addressing the problem of optimization in the complex domain, fully developing a framework that enables taking full advantage of the power of complex-valued processing. Then, the challenges of multichannel processing of complex-valued signals are explored. This comprehensive volume goes on to cover Turbo processing, tracking in the subspace domain, nonlinear sequential state estimation, and speech-bandwidth extension. Examines the seven most important topics in adaptive filtering that will define the next-generation adaptive filtering solutions Introduces the powerful adaptive signal processing methods developed within the last ten years to account for the characteristics of real-life data: non-Gaussianity, non-circularity, non-stationarity, and non-linearity Features self-contained chapters, numerous examples to clarify concepts, and end-of-chapter problems to reinforce understanding of the material Contains contributions from acknowledged leaders in the field Adaptive Signal Processing is an invaluable tool for graduate students, researchers, and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.
Jiri Tuma Vehicle Gearbox Noise and Vibration. Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures Jiri Tuma Vehicle Gearbox Noise and Vibration. Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures Новинка

Jiri Tuma Vehicle Gearbox Noise and Vibration. Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures

9598.21 руб.
Advances in methods of gear design and the possibility of predicting the sound pressure level and life time of gearboxes and perfect instrumentation of test stands allows for the production of a new generation of quiet transmission units. Current literature on gearbox noise and vibration is usually focused on a particular problem such as gearbox design without a detailed description of measurement methods for noise and vibration testing. Vehicle Gearbox Noise and Vibration: Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures addresses this need and comprehensively covers the sources of noise and vibration in gearboxes and describes various methods of signal processing. It also covers gearing design, precision manufacturing, measuring the gear train transmission error, noise test on testing stands and also during vehicle pass-by tests. The analysis tools for gearbox inspection are based on the frequency and time domain methods, including envelope and average toothmesh analysis. To keep the radiated noise under control, the effect of load, the gear contact ratio and the tooth surface modification on noise and vibration are illustrated by measurement examples giving an idea how to reduce transmission noise. Key features: Covers methods of processing noise and vibration signals Takes a practical approach to the subject and includes a case study covering how to successfully reduce transmission noise Describes the procedure for the measurement and calculation of the angular vibrations of gears during rotation Considers various signal processing methods including order analysis, synchronous averaging, Vold-Kalman order tracking filtration and measuring the angular vibration Vehicle Gearbox Noise and Vibration: Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures is a comprehensive reference for designers of gearing systems and test engineers in the automotive industry and is also a useful source of information for graduate students in automotive and noise engineering.
He You Radar Data Processing With Applications He You Radar Data Processing With Applications Новинка

He You Radar Data Processing With Applications

11997.76 руб.
A systematic introduction to the theory, development and latest research results of radar data processing technology • Presents both classical theory and development methods of radar data processing • Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory • Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar • Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command
Sudharman Jayaweera K. Signal Processing for Cognitive Radios Sudharman Jayaweera K. Signal Processing for Cognitive Radios Новинка

Sudharman Jayaweera K. Signal Processing for Cognitive Radios

10123.22 руб.
This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.
Jacob Benesty Fundamentals of Signal Enhancement and Array Signal Processing Jacob Benesty Fundamentals of Signal Enhancement and Array Signal Processing Новинка

Jacob Benesty Fundamentals of Signal Enhancement and Array Signal Processing

10123.22 руб.
A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals Systematically introduces the fundamental principles, theory and applications of signal enhancement and array signal processing in an accessible manner Offers an updated and relevant treatment of array signal processing with rigor and concision Features a companion website that includes presentation files with lecture notes, homework exercises, course projects, solution manuals, instructor manuals, and Matlab codes for the examples in the book
Ravi Jaiswal Particle Adhesion and Removal Ravi Jaiswal Particle Adhesion and Removal Новинка

Ravi Jaiswal Particle Adhesion and Removal

15067.45 руб.
The book provides a comprehensive and easily accessible reference source covering all important aspects of particle adhesion and removal. The core objective is to cover both fundamental and applied aspects of particle adhesion and removal with emphasis on recent developments. Among the topics to be covered include: 1. Fundamentals of surface forces in particle adhesion and removal. 2. Mechanisms of particle adhesion and removal. 3. Experimental methods (e.g. AFM, SFA,SFM,IFM, etc.) to understand particle-particle and particle-substrate interactions. 4. Mechanics of adhesion of micro- and nanoscale particles. 5. Various factors affecting particle adhesion to a variety of substrates. 6. Surface modification techniques to modulate particle adhesion. 7. Various cleaning methods (both wet & dry) for particle removal. 8. Relevance of particle adhesion in a host of technologies ranging from simple to ultra-sophisticated.
Ali Akansu N. Financial Signal Processing and Machine Learning Ali Akansu N. Financial Signal Processing and Machine Learning Новинка

Ali Akansu N. Financial Signal Processing and Machine Learning

8041.67 руб.
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
Lawson Andrew B. Bayesian Biostatistics Lawson Andrew B. Bayesian Biostatistics Новинка

Lawson Andrew B. Bayesian Biostatistics

6207.19 руб.
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials. Key Features: Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas of application. Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics. Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs. Highlights the differences between the Bayesian and classical approaches. Supported by an accompanying website hosting free software and case study guides. Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.
Johannes Stahl Single Channel Phase-Aware Signal Processing in Speech Communication. Theory and Practice Johannes Stahl Single Channel Phase-Aware Signal Processing in Speech Communication. Theory and Practice Новинка

Johannes Stahl Single Channel Phase-Aware Signal Processing in Speech Communication. Theory and Practice

7734.34 руб.
An overview on the challenging new topic of phase-aware signal processing Speech communication technology is a key factor in human-machine interaction, digital hearing aids, mobile telephony, and automatic speech/speaker recognition. With the proliferation of these applications, there is a growing requirement for advanced methodologies that can push the limits of the conventional solutions relying on processing the signal magnitude spectrum. Single-Channel Phase-Aware Signal Processing in Speech Communication provides a comprehensive guide to phase signal processing and reviews the history of phase importance in the literature, basic problems in phase processing, fundamentals of phase estimation together with several applications to demonstrate the usefulness of phase processing. Key features: Analysis of recent advances demonstrating the positive impact of phase-based processing in pushing the limits of conventional methods. Offers unique coverage of the historical context, fundamentals of phase processing and provides several examples in speech communication. Provides a detailed review of many references and discusses the existing signal processing techniques required to deal with phase information in different applications involved with speech. The book supplies various examples and MATLAB® implementations delivered within the PhaseLab toolbox. Single-Channel Phase-Aware Signal Processing in Speech Communication is a valuable single-source for students, non-expert DSP engineers, academics and graduate students.
William Bolstad M. Introduction to Bayesian Statistics William Bolstad M. Introduction to Bayesian Statistics Новинка

William Bolstad M. Introduction to Bayesian Statistics

10497.42 руб.
"…this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
Thomas Kaiser Digital Signal Processing for RFID Thomas Kaiser Digital Signal Processing for RFID Новинка

Thomas Kaiser Digital Signal Processing for RFID

8997.79 руб.
This book discusses the fundamentals of RFID and the state-of-the-art research results in signal processing for RFID, including MIMO, blind source separation, anti-collision, localization, covert RFID and chipless RFID. Aimed at graduate students as well as academic and professional researchers/engineers in RFID technology, it enables readers to become conversant with the latest theory and applications of signal processing for RFID. Key Features: Provides a systematic and comprehensive insight into the application of modern signal processing techniques for RFID systems Discusses the operating principles, channel models of RFID, RFID protocols and analog/digital filter design for RFID Explores RFID-oriented modulation schemes and their performance Highlights research fields such as MIMO for RFID, blind signal processing for RFID, anti-collision of multiple RFID tags, localization with RFID, covert RFID and chipless RFID Contains tables, illustrations and design examples
Donald Reay S. Digital Signal Processing Using the ARM Cortex M4 Donald Reay S. Digital Signal Processing Using the ARM Cortex M4 Новинка

Donald Reay S. Digital Signal Processing Using the ARM Cortex M4

6744.78 руб.
Features inexpensive ARM® Cortex®-M4 microcontroller development systems available from Texas Instruments and STMicroelectronics. This book presents a hands-on approach to teaching Digital Signal Processing (DSP) with real-time examples using the ARM® Cortex®-M4 32-bit microprocessor. Real-time examples using analog input and output signals are provided, giving visible (using an oscilloscope) and audible (using a speaker or headphones) results. Signal generators and/or audio sources, e.g. iPods, can be used to provide experimental input signals. The text also covers the fundamental concepts of digital signal processing such as analog-to-digital and digital-to-analog conversion, FIR and IIR filtering, Fourier transforms, and adaptive filtering. Digital Signal Processing Using the ARM® Cortex®-M4: Uses a large number of simple example programs illustrating DSP concepts in real-time, in an electrical engineering laboratory setting Includes examples for both STM32F407 Discovery and the TM4C123 Launchpad, using Keil MDK-ARM, on a companion website Example programs for the TM4C123 Launchpad using Code Composer Studio version 6 available on companion website Digital Signal Processing Using the ARM® Cortex®-M4 serves as a teaching aid for university professors wishing to teach DSP using laboratory experiments, and for students or engineers wishing to study DSP using the inexpensive ARM® Cortex®-M4. Donald Reay is a lecturer in electrical engineering at Heriot-Watt University in Edinburgh, Scotland. He has also taught hands-on DSP, on a number of occasions, as a visiting lecturer at Zhejiang University in Hangzhou, China. He co-authored Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, Second Edition (Wiley 2008) with Rulph Chassaing, and is the author of Digital Signal Processing and Applications with the OMAP-L138 eXperimenter (Wiley 2012).
Umberto Spagnolini Statistical Signal Processing in Engineering Umberto Spagnolini Statistical Signal Processing in Engineering Новинка

Umberto Spagnolini Statistical Signal Processing in Engineering

10497.42 руб.
A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application. Uniquely, Statistical Signal Processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students’ analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions. Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statistical signal processing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice Includes MATLAB code of many of the experiments in the book Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an ideal text for engineering students at large, applied mathematics post-graduates and advanced undergraduates in electrical engineering, applied statistics, and pure mathematics, studying statistical signal processing.
Boccaccini Aldo R. Ceramics and Composites Processing Methods Boccaccini Aldo R. Ceramics and Composites Processing Methods Новинка

Boccaccini Aldo R. Ceramics and Composites Processing Methods

14713.34 руб.
Examines the latest processing and fabrication methods There is increasing interest in the application of advanced ceramic materials in diverse areas such as transportation, energy, environmental protection and remediation, communications, health, and aerospace. This book guides readers through a broad selection of key processing techniques for ceramics and their composites, enabling them to manufacture ceramic products and components with the properties needed for various industrial applications. With chapters contributed by internationally recognized experts in the field of ceramics, the book includes traditional fabrication routes as well as new and emerging approaches in order to meet the increasing demand for more reliable ceramic materials. Ceramics and Composites Processing Methods is divided into three sections: Densification, covering the fundamentals and practice of sintering, pulsed electric current sintering, and viscous phase silicate processing Chemical Methods, examining colloidal methods, sol-gel, gel casting, polymer processing, chemical vapor deposition, chemical vapor infiltration, reactive melt infiltration, and combustion synthesis Physical Methods, including directional solidification, solid free-form fabrication, microwave processing, electrophoretic deposition, and plasma spraying Each chapter focuses on a particular processing method or approach. Collectively, these chapters offer readers comprehensive, state-of-the-science information on the many approaches, techniques, and methods for the processing and fabrication of advanced ceramics and ceramic composites. With its coverage of the latest processing methods, Ceramics and Composites Processing Methods is recommended for researchers and students in ceramics, materials science, structural materials, biomedical engineering, and nanotechnology.
Simon Jackman Bayesian Analysis for the Social Sciences Simon Jackman Bayesian Analysis for the Social Sciences Новинка

Simon Jackman Bayesian Analysis for the Social Sciences

7126.78 руб.
Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS – the most-widely used Bayesian analysis software in the world – and R – an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.
Eugene Hahn D. Bayesian Methods for Management and Business. Pragmatic Solutions for Real Problems Eugene Hahn D. Bayesian Methods for Management and Business. Pragmatic Solutions for Real Problems Новинка

Eugene Hahn D. Bayesian Methods for Management and Business. Pragmatic Solutions for Real Problems

9672.91 руб.
HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments. Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage. Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems also features: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systems An incremental skill-building presentation based on analyzing data sets with widely applicable models of increasing complexity An accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problems A practical problem-solving approach to illustrate how Bayesian statistics can help to provide insight into important issues facing business and management Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who seek to broaden their methodological skill sets.
Roger Woods FPGA-based Implementation of Signal Processing Systems Roger Woods FPGA-based Implementation of Signal Processing Systems Новинка

Roger Woods FPGA-based Implementation of Signal Processing Systems

8997.79 руб.
An important working resource for engineers and researchers involved in the design, development, and implementation of signal processing systems The last decade has seen a rapid expansion of the use of field programmable gate arrays (FPGAs) for a wide range of applications beyond traditional digital signal processing (DSP) systems. Written by a team of experts working at the leading edge of FPGA research and development, this second edition of FPGA-based Implementation of Signal Processing Systems has been extensively updated and revised to reflect the latest iterations of FPGA theory, applications, and technology. Written from a system-level perspective, it features expert discussions of contemporary methods and tools used in the design, optimization and implementation of DSP systems using programmable FPGA hardware. And it provides a wealth of practical insights—along with illustrative case studies and timely real-world examples—of critical concern to engineers working in the design and development of DSP systems for radio, telecommunications, audio-visual, and security applications, as well as bioinformatics, Big Data applications, and more. Inside you will find up-to-date coverage of: FPGA solutions for Big Data Applications, especially as they apply to huge data sets The use of ARM processors in FPGAs and the transfer of FPGAs towards heterogeneous computing platforms The evolution of High Level Synthesis tools—including new sections on Xilinx's HLS Vivado tool flow and Altera's OpenCL approach Developments in Graphical Processing Units (GPUs), which are rapidly replacing more traditional DSP systems FPGA-based Implementation of Signal Processing Systems, 2nd Edition is an indispensable guide for engineers and researchers involved in the design and development of both traditional and cutting-edge data and signal processing systems. Senior-level electrical and computer engineering graduates studying signal processing or digital signal processing also will find this volume of great interest.
Mahendra Mallick Integrated Tracking, Classification, and Sensor Management. Theory and Applications Mahendra Mallick Integrated Tracking, Classification, and Sensor Management. Theory and Applications Новинка

Mahendra Mallick Integrated Tracking, Classification, and Sensor Management. Theory and Applications

11997.76 руб.
A unique guide to the state of the art of tracking, classification, and sensor management This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques. Features include: An accessible coverage of random finite set based multi-target filtering algorithms such as the Probability Hypothesis Density filters and multi-Bernoulli filters with focus on problem solving A succinct overview of the track-oriented MHT that comprehensively collates all significant developments in filtering and tracking A state-of-the-art algorithm for hybrid Bayesian network (BN) inference that is efficient and scalable for complex classification models New structural results in stochastic sensor scheduling and algorithms for dynamic sensor scheduling and management Coverage of the posterior Cramer-Rao lower bound (PCRLB) for target tracking and sensor management Insight into cutting-edge military and civilian applications, including intelligence, surveillance, and reconnaissance (ISR) With its emphasis on the latest research results, Integrated Tracking, Classification, and Sensor Management is an invaluable guide for researchers and practitioners in statistical signal processing, radar systems, operations research, and control theory.
Nicolae-Doru Stanescu Classical and Modern Approaches in the Theory of Mechanisms Nicolae-Doru Stanescu Classical and Modern Approaches in the Theory of Mechanisms Новинка

Nicolae-Doru Stanescu Classical and Modern Approaches in the Theory of Mechanisms

8963.64 руб.
Classical and Modern Approaches in the Theory of Mechanisms is a study of mechanisms in the broadest sense, covering the theoretical background of mechanisms, their structures and components, the planar and spatial analysis of mechanisms, motion transmission, and technical approaches to kinematics, mechanical systems, and machine dynamics. In addition to classical approaches, the book presents two new methods: the analytic-assisted method using Turbo Pascal calculation programs, and the graphic-assisted method, outlining the steps required for the development of graphic constructions using AutoCAD; the applications of these methods are illustrated with examples. Aimed at students of mechanical engineering, and engineers designing and developing mechanisms in their own fields, this book provides a useful overview of classical theories, and modern approaches to the practical and creative application of mechanisms, in seeking solutions to increasingly complex problems.
Francis Castanié Digital Spectral Analysis. Parametric, Non-Parametric and Advanced Methods Francis Castanié Digital Spectral Analysis. Parametric, Non-Parametric and Advanced Methods Новинка

Francis Castanié Digital Spectral Analysis. Parametric, Non-Parametric and Advanced Methods

12644.28 руб.
Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature. The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators. Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids. Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.
Mohammad Nakhostin Signal Processing for Radiation Detectors Mohammad Nakhostin Signal Processing for Radiation Detectors Новинка

Mohammad Nakhostin Signal Processing for Radiation Detectors

10872.33 руб.
Presents the fundamental concepts of signal processing for all application areas of ionizing radiation This book provides a clear understanding of the principles of signal processing of radiation detectors. It puts great emphasis on the characteristics of pulses from various types of detectors and offers a full overview on the basic concepts required to understand detector signal processing systems and pulse processing techniques. Signal Processing for Radiation Detectors covers all of the important aspects of signal processing, including energy spectroscopy, timing measurements, position-sensing, pulse-shape discrimination, and radiation intensity measurement. The book encompasses a wide range of applications so that readers from different disciplines can benefit from all of the information. In addition, this resource: Describes both analog and digital techniques of signal processing Presents a complete compilation of digital pulse processing algorithms Extrapolates content from more than 700 references covering classic papers as well as those of today Demonstrates concepts with more than 340 original illustrations Signal Processing for Radiation Detectors provides researchers, engineers, and graduate students working in disciplines such as nuclear physics and engineering, environmental and biomedical engineering, and medical physics and radiological science, the knowledge to design their own systems, optimize available systems or to set up new experiments.
Eric Hansen W. Fourier Transforms. Principles and Applications Eric Hansen W. Fourier Transforms. Principles and Applications Новинка

Eric Hansen W. Fourier Transforms. Principles and Applications

10497.42 руб.
Fourier Transforms: Principles and Applications explains transform methods and their applications to electrical systems from circuits, antennas, and signal processors—ably guiding readers from vector space concepts through the Discrete Fourier Transform (DFT), Fourier series, and Fourier transform to other related transform methods. Featuring chapter end summaries of key results, over two hundred examples and four hundred homework problems, and a Solutions Manual this book is perfect for graduate students in signal processing and communications as well as practicing engineers. Class-tested at Dartmouth Provides the same solid background as classic texts in the field, but with an emphasis on digital and other contemporary applications to signal and image processing Modular coverage of material allows for topics to be covered by preference MATLAB files and Solutions Manual available to instructors Over 300 figures, 200 worked examples, and 432 homework problems
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.
Hussein Baher Signal Processing and Integrated Circuits Hussein Baher Signal Processing and Integrated Circuits Новинка

Hussein Baher Signal Processing and Integrated Circuits

7586.57 руб.
This book provides a balanced account of analog, digital and mixed-mode signal processing with applications in telecommunications. Part I Perspective gives an overview of the areas of Systems on a Chip (Soc) and mobile communication which are used to demonstrate the complementary relationship between analog and digital systems. Part II Analog (continuous-time) and Digital Signal Processing contains both fundamental and advanced analysis, and design techniques, of analog and digital systems. This includes analog and digital filter design; fast Fourier transform (FFT) algorithms; stochastic signals; linear estimation and adaptive filters. Part III Analog MOS Integrated Circuits for Signal Processing covers basic MOS transistor operation and fabrication through to the design of complex integrated circuits such as high performance Op Amps, Operational Transconductance Amplifiers (OTA's) and Gm-C circuits. Part IV Switched-capacitor and Mixed-mode Signal Processing outlines the design of switched-capacitor filters, and concludes with sigma-delta data converters as an extensive application of analog and digital signal processing Contains the fundamentals and advanced techniques of continuous-time and discrete-time signal processing. Presents in detail the design of analog MOS integrated circuits for signal processing, with application to the design of switched-capacitor filters. Uses the comprehensive design of integrated sigma-delta data converters to illustrate and unify the techniques of signal processing. Includes solved examples, end of chapter problems and MATLAB® throughout the book, to help readers understand the mathematical complexities of signal processing. The treatment of the topic is at the senior undergraduate to graduate and professional levels, with sufficient introductory material for the book to be used as a self-contained reference.
J. Parker R. Algorithms for Image Processing and Computer Vision J. Parker R. Algorithms for Image Processing and Computer Vision Новинка

J. Parker R. Algorithms for Image Processing and Computer Vision

7280.04 руб.
A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.
Jean-Christophe Valière Acoustic Particle Velocity Measurements Using Laser. Principles, Signal Processing and Applications Jean-Christophe Valière Acoustic Particle Velocity Measurements Using Laser. Principles, Signal Processing and Applications Новинка

Jean-Christophe Valière Acoustic Particle Velocity Measurements Using Laser. Principles, Signal Processing and Applications

6448.84 руб.
This book concerns the presentation of particle velocity measurement for acoustics using lasers, including Laser Doppler Velocimetry (LDV or Anemometry (LDA)) and Particle Imagery Velocimetry (PIV). The objective is first to present the importance of measuring the acoustic velocity, especially when the acoustic equations are nonlinear as well as characterizing the near fields. However, these applications need to use non-invasive sensors. Some optical techniques, initially developed for fluid mechanics, have been adapted to the field of acoustics in recent years. This book summarizes 15 years of research in this area, highlighting the improvements that have been made, particularly in signal processing, and showing applications for which they have proven to be a carrier of innovation.
Saeid Sanei Adaptive Processing of Brain Signals Saeid Sanei Adaptive Processing of Brain Signals Новинка

Saeid Sanei Adaptive Processing of Brain Signals

9972.41 руб.
In this book, the field of adaptive learning and processing is extended to arguably one of its most important contexts which is the understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing methods are developed and used to assist clinical findings. Recent developments in detection, estimation and separation of diagnostic cues from different modality neuroimaging systems are discussed. These include constrained nonlinear signal processing techniques which incorporate sparsity, nonstationarity, multimodal data, and multiway techniques. Key features: Covers advanced and adaptive signal processing techniques for the processing of electroencephalography (EEG) and magneto-encephalography (MEG) signals, and their correlation to the corresponding functional magnetic resonance imaging (fMRI) Provides advanced tools for the detection, monitoring, separation, localising and understanding of functional, anatomical, and physiological abnormalities of the brain Puts a major emphasis on brain dynamics and how this can be evaluated for the assessment of brain activity in various states such as for brain-computer interfacing emotions and mental fatigue analysis Focuses on multimodal and multiway adaptive processing of brain signals, the new direction of brain signal research
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.
Prasanna Kalansuriya Chipless Radio Frequency Identification Reader Signal Processing Prasanna Kalansuriya Chipless Radio Frequency Identification Reader Signal Processing Новинка

Prasanna Kalansuriya Chipless Radio Frequency Identification Reader Signal Processing

9372.7 руб.
Presents a comprehensive overview and analysis of the recent developments in signal processing for Chipless Radio Frequency Identification Systems This book presents the recent research results on Radio Frequency Identification (RFID) and provides smart signal processing methods for detection, signal integrity, multiple-access and localization, tracking, and collision avoidance in Chipless RFID systems. The book is divided into two sections: The first section discusses techniques for detection and denoising in Chipless RFID systems. These techniques include signal space representation, detection of frequency signatures using UWB impulse radio interrogation, time domain analysis, singularity expansion method for data extraction, and noise reduction and filtering techniques. The second section covers collision and error correction protocols, multi-tag identification through time-frequency analysis, FMCW radar based collision detection and multi-access for Chipless RFID tags as we as localization and tag tracking. Describes the use of UWB impulse radio interrogation to remotely estimate the frequency signature of Chipless RFID tags using the backscatter principle Reviews the collision problem in both chipped and Chipless RFID systems and summarizes the prevailing anti-collision algorithms to address the problem Proposes state-of-the-art multi-access and signal integrity protocols to improve the efficacy of the system in multiple tag reading scenarios Features an industry approach to the integration of various systems of the Chipless RFID reader-integration of physical layers, middleware, and enterprise software Chipless Radio Frequency Identification Reader Signal Processing is primarily written for researchers in the field of RF sensors but can serve as supplementary reading for graduate students and professors in electrical engineering and wireless communications.
Smain Femmam Fundamentals of Signals and Control Systems Smain Femmam Fundamentals of Signals and Control Systems Новинка

Smain Femmam Fundamentals of Signals and Control Systems

11997.76 руб.
The aim of this book is the study of signals and deterministic systems, linear, time-invariant, finite dimensions and causal. A set of useful tools is selected for the automatic and signal processing and methods of representation of dynamic linear systems are exposed, and analysis of their behavior. Finally we discuss the estimation, identification and synthesis of control laws for the purpose of stabilization and regulation. The study of signal characteristics and properties systems and knowledge of mathematical tools and treatment methods and analysis, are lately more and more importance and continue to evolve. The reason is that the current state of technology, particularly electronics and computing, enables the production of very advanced processing systems, effective and less expensive despite the complexity.
Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications Новинка

Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications

11494.8 руб.
The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications Новинка

Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications

14996.31 руб.
This book presents a comprehensive overview of relative fidelity preservation processing methods and their applications within the oil and gas sector. Four key principles for wide-frequency relative fidelity preservation processing are illustrated throughout the text. Seismic broadband acquisition is the basis for relative fidelity preservation processing and the influence of seismic acquisition on data processing is also analyzed. The methods and principles of Kirchhoff integral migration, one-way wave equation migration and reverse time migration are also introduced and illustrated clearly. Current research of relative amplitude preservation migration algorithms is introduced, and the corresponding numerical results are also shown. RTM (reverse time migration) imaging methods based on GPU/CPU systems for complicated structures are represented. This includes GPU/CPU high performance calculations and its application to seismic exploration, two-way wave extrapolation operator and boundary conditions, imaging conditions and low frequency noise attenuation, and GPU/CPU system based RTM imaging algorithms. Migration velocity model building methods in depth domain for complicated structures are illustrated in this book. The research status and development of velocity model building are introduced. And the impacting factors are also discussed. Several different velocity model building methods are also represented and analyzed. The book also provides the reader with several case studies of field seismic data imaging in different kinds of basins to show the methods used in practice.
John Leis W. Digital Signal Processing Using MATLAB for Students and Researchers John Leis W. Digital Signal Processing Using MATLAB for Students and Researchers Новинка

John Leis W. Digital Signal Processing Using MATLAB for Students and Researchers

8425.69 руб.
Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges. Following an introductory chapter, the text explores: Sampled signals and digital processing Random signals Representing signals and systems Temporal and spatial signal processing Frequency analysis of signals Discrete-time filters and recursive filters Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth. Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed.
Xiaolan Qiu Bistatic SAR Data Processing Algorithms Xiaolan Qiu Bistatic SAR Data Processing Algorithms Новинка

Xiaolan Qiu Bistatic SAR Data Processing Algorithms

11997.76 руб.
Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so signal processing is more challenging. Focusing on imaging aspects of bistatic SAR signal processing, this book covers resolution analysis, echo generation methods, imaging algorithms, imaging parameter estimation, and motion compensation methods. The book is ideal for researchers and engineers in SAR signal and data processing, as well as those working in bistatic and multistatic radar imaging, and in the radar sciences. Graduate students with a background in radar who are interested in bistatic and multistatic radar will find this book a helpful reference. Gives a general and updated framework for image formation using signal processing aspects Starts with an introduction to traditional SAR before moving on to more advanced topics Offers readers a range of exhaustive tools to process signals and form images Provides a solid reference for the imaging of other complicated SAR Sample image synthesis exercises are available from the book's companion site
Matt Sekerke Bayesian Risk Management. A Guide to Model Risk and Sequential Learning in Financial Markets Matt Sekerke Bayesian Risk Management. A Guide to Model Risk and Sequential Learning in Financial Markets Новинка

Matt Sekerke Bayesian Risk Management. A Guide to Model Risk and Sequential Learning in Financial Markets

6066.7 руб.
A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.
Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis Новинка

Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis

7873.78 руб.
Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.
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.
Yinao Su Measurement While Drilling (MWD) Signal Analysis, Optimization and Design Yinao Su Measurement While Drilling (MWD) Signal Analysis, Optimization and Design Новинка

Yinao Su Measurement While Drilling (MWD) Signal Analysis, Optimization and Design

15067.45 руб.
Trade magazines and review articles describe MWD in casual terms, e.g., positive versus negative pulsers, continuous wave systems, drilling channel noise and attenuation, in very simple terms absent of technical rigor. However, few truly scientific discussions are available on existing methods, let alone the advances necessary for high-data-rate telemetry. Without a strong foundation building on solid acoustic principles, rigorous mathematics, and of course, fast, inexpensive and efficient testing of mechanical designs, low data rates will impose unacceptable quality issues to real-time formation evaluation for years to come. This book promises to change all of this. The lead author and M.I.T. educated scientist, Wilson Chin, and Yinao Su, Academician, Chinese Academy of Engineering, and other team members, have written the only book available that develops mud pulse telemetry from first principles, adapting sound acoustic principles to rigorous signal processing and efficient wind tunnel testing. In fact, the methods and telemetry principles developed in the book were recently adopted by one of the world’s largest industrial corporations in its mission to redefine the face of MWD. The entire engineering history for continuous wave telemetry is covered: anecdotal stories and their fallacies, original hardware problems and their solutions, different noise mechanisms and their signal processing solutions, apparent paradoxes encountered in field tests and simple explanations to complicated questions, and so on, are discussed in complete “tell all” detail for students, research professors and professional engineers alike. These include signal processing algorithms, signal enhancement methods, and highly efficient “short” and “long wind tunnel” test methods, whose results can be dynamically re-scaled to real muds flowing at any speed. A must read for all petroleum engineering professionals!
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.
Wilson Chin C. Measurement While Drilling. Signal Analysis, Optimization and Design Wilson Chin C. Measurement While Drilling. Signal Analysis, Optimization and Design Новинка

Wilson Chin C. Measurement While Drilling. Signal Analysis, Optimization and Design

15901.14 руб.
Trade magazines and review articles describe MWD in casual terms, e.g., positive versus negative pulsers, continuous wave systems, drilling channel noise and attenuation, in very simple terms absent of technical rigor. However, few truly scientific discussions are available on existing methods, let alone the advances necessary for high-data-rate telemetry. Without a strong foundation building on solid acoustic principles, rigorous mathematics, and of course, fast, inexpensive and efficient testing of mechanical designs, low data rates will impose unacceptable quality issues to real-time formation evaluation for years to come. This all-new revised second edition of an instant classic promises to change all of this. The lead author and M.I.T.-educated scientist, Wilson Chin, has written the only book available that develops mud pulse telemetry from first principles, adapting sound acoustic principles to rigorous signal processing and efficient wind tunnel testing. In fact, the methods and telemetry principles developed in the book were recently adopted by one of the world’s largest industrial corporations in its mission to redefine the face of MWD. The entire engineering history for continuous wave telemetry is covered: anecdotal stories and their fallacies, original hardware problems and their solutions, different noise mechanisms and their signal processing solutions, apparent paradoxes encountered in field tests and simple explanations to complicated questions, and so on, are discussed in complete “tell all” detail for students, research professors and professional engineers alike. These include signal processing algorithms, signal enhancement methods, and highly efficient “short” and “long wind tunnel” test methods, whose results can be dynamically re-scaled to real muds flowing at any speed. A must read for all petroleum engineering professionals!
Jacques Lamon Processing and Properties of Advanced Ceramics and Composites III Jacques Lamon Processing and Properties of Advanced Ceramics and Composites III Новинка

Jacques Lamon Processing and Properties of Advanced Ceramics and Composites III

10497.42 руб.
This book contains 17 papers from the Innovative Processing and Synthesis of Ceramics, Glasses and Composites and Advances in Ceramic Matrix Composites symposia held during the 2010 Materials Science and Technology (MS&T'10) meeting, October 17-21, 2010, Houston, Texas. Topics include: Fiber Composites; Modeling and Characterization; Nanomaterials; Testing; Microstructure-Property Relationships; Advanced Coatings; and Processing Methods.
Zhengyou He Wavelet Analysis and Transient Signal Processing Applications for Power Systems Zhengyou He Wavelet Analysis and Transient Signal Processing Applications for Power Systems Новинка

Zhengyou He Wavelet Analysis and Transient Signal Processing Applications for Power Systems

9748.31 руб.
An original reference applying wavelet analysis to power systems engineering • Introduces a modern signal processing method called wavelet analysis, and more importantly, its applications to power system fault detection and protection • Concentrates on its application to the power system, offering great potential for fault detection and protection • Presents applications, examples, and case studies, together with the latest research findings • Provides a combination of the author’s tutorial notes from electrical engineering courses together with his own original research work, of interest to both industry and academia
Lorenz Biegler Large-Scale Inverse Problems and Quantification of Uncertainty Lorenz Biegler Large-Scale Inverse Problems and Quantification of Uncertainty Новинка

Lorenz Biegler Large-Scale Inverse Problems and Quantification of Uncertainty

11696.84 руб.
This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: • Brings together the perspectives of researchers in areas of inverse problems and data assimilation. • Assesses the current state-of-the-art and identify needs and opportunities for future research. • Focuses on the computational methods used to analyze and simulate inverse problems. • Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.
Peter Lee M. Bayesian Statistics. An Introduction Peter Lee M. Bayesian Statistics. An Introduction Новинка

Peter Lee M. Bayesian Statistics. An Introduction

4900.62 руб.
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples. This edition: Includes expanded coverage of Gibbs sampling, including more numerical examples and treatments of OpenBUGS, R2WinBUGS and R2OpenBUGS. Presents significant new material on recent techniques such as Bayesian importance sampling, variational Bayes, Approximate Bayesian Computation (ABC) and Reversible Jump Markov Chain Monte Carlo (RJMCMC). Provides extensive examples throughout the book to complement the theory presented. Accompanied by a supporting website featuring new material and solutions. More and more students are realizing that they need to learn Bayesian statistics to meet their academic and professional goals. This book is best suited for use as a main text in courses on Bayesian statistics for third and fourth year undergraduates and postgraduate students.
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.
Ioannis Ntzoufras Bayesian Modeling Using WinBUGS Ioannis Ntzoufras Bayesian Modeling Using WinBUGS Новинка

Ioannis Ntzoufras Bayesian Modeling Using WinBUGS

12337.75 руб.
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all data sets and code are available on the book's related Web site. Requiring only a working knowledge of probability theory and statistics, Bayesian Modeling Using WinBUGS serves as an excellent book for courses on Bayesian statistics at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of statistics, actuarial science, medicine, and the social sciences who use WinBUGS in their everyday work.
Qi Wang Visible Light Communications. Modulation and Signal Processing Qi Wang Visible Light Communications. Modulation and Signal Processing Новинка

Qi Wang Visible Light Communications. Modulation and Signal Processing

9748.31 руб.
A complete and comprehensive reference on modulation and signal processing for visible light communication This informative new book on state-of-the-art visible light communication (VLC) provides, for the first time, a systematical and advanced treatment of modulation and signal processing for VLC. Visible Light Communications: Modulation and Signal Processing offers a practical guide to designing VLC, linking academic research with commercial applications. In recent years, VLC has attracted attention from academia and industry since it has many advantages over the traditional radio frequency, including wide unregulated bandwidth, high security, and low cost. It is a promising complementary technique in 5G and beyond wireless communications, especially in indoor applications. However, lighting constraints have not been fully considered in the open literature when considering VLC system design, and its importance has been underestimated. That’s why this book—written by a team of experts with both academic research experience and industrial development experience in the field—is so welcome. To help readers understand the theory and design of VLC systems, the book: Details many modern techniques on both modulation and signal processing aspects Links academic research with commercial applications in visible light communications as well as other wireless communication systems Combines theoretical rigor with practical examples in presenting optical camera communication systems Visible Light Communications: Modulation and Signal Processing serves as a useful tool and reference book for visible light communication professionals, as well as wireless communication system professionals and project managers. It is also an important guide for undergraduates and graduates who want to conduct research in areas of wireless communications.
Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Новинка

Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods

9897.71 руб.
A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
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.
Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Новинка

Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods

10115.42 руб.
A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
Enrique Saldivar-Guerra Handbook of Polymer Synthesis, Characterization, and Processing Enrique Saldivar-Guerra Handbook of Polymer Synthesis, Characterization, and Processing Новинка

Enrique Saldivar-Guerra Handbook of Polymer Synthesis, Characterization, and Processing

16046.34 руб.
Covering a broad range of polymer science topics, Handbook of Polymer Synthesis, Characterization, and Processing provides polymer industry professionals and researchers in polymer science and technology with a single, comprehensive handbook summarizing all aspects involved in the polymer production chain. The handbook focuses on industrially important polymers, analytical techniques, and formulation methods, with chapters covering step-growth, radical, and co-polymerization, crosslinking and grafting, reaction engineering, advanced technology applications, including conjugated, dendritic, and nanomaterial polymers and emulsions, and characterization methods, including spectroscopy, light scattering, and microscopy.
Huijun Gao Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information Huijun Gao Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information Новинка

Huijun Gao Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information

11622.14 руб.
In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information reflects the state-of-the-art of the research area for handling randomly occurring incomplete information from three interrelated aspects of control, filtering and fault detection. Recent advances in networked control systems and distributed filtering over sensor networks are covered, and application potential in mobile robotics is also considered. The reader will benefit from the introduction of new concepts, new models and new methodologies with practical significance in control engineering and signal processing. Key Features: Establishes a unified framework for filtering, control and fault detection problem for various discrete-time nonlinear stochastic systems with randomly occurring incomplete information Investigates several new concepts for randomly occurring phenomena and proposes a new system model to better describe network-induced problems Demonstrates how newly developed techniques can handle emerging mathematical and computational challenges Contains the latest research results Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information provides a unified yet neat framework for control/filtering/fault-detection with randomly occurring incomplete information. It is a comprehensive textbook for graduate students and is also a useful practical research reference for engineers dealing with control, filtering and fault detection problems for networked systems.
Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach Новинка

Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach

6973.51 руб.
A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course
Palmiro Poltronieri Microbiology in Dairy Processing. Challenges and Opportunities Palmiro Poltronieri Microbiology in Dairy Processing. Challenges and Opportunities Новинка

Palmiro Poltronieri Microbiology in Dairy Processing. Challenges and Opportunities

14996.31 руб.
An authoritative guide to microbiological solutions to common challenges encountered in the industrial processing of milk and the production of milk products Microbiology in Dairy Processing offers a comprehensive introduction to the most current knowledge and research in dairy technologies and lactic acid bacteria (LAB) and dairy associated species in the fermentation of dairy products. The text deals with the industrial processing of milk, the problems solved in the industry, and those still affecting the processes. The authors explore culture methods and species selective growth media, to grow, separate, and characterize LAB and dairy associated species, molecular methods for species identification and strains characterization, Next Generation Sequencing for genome characterization, comparative genomics, phenotyping, and current applications in dairy and non-dairy productions. In addition, Microbiology in Dairy Processing covers the Lactic Acid Bacteria and dairy associated species (the beneficial microorganisms used in food fermentation processes): culture methods, phenotyping, and proven applications in dairy and non-dairy productions. The text also reviews the potential future exploitation of the culture of novel strains with useful traits such as probiotics, fermentation of sugars, metabolites produced, bacteriocins. This important resource: Offers solutions both established and novel to the numerous challenges commonly encountered in the industrial processing of milk and the production of milk products Takes a highly practical approach, tackling the problems faced in the workplace by dairy technologists Covers the whole chain of dairy processing from milk collection and storage though processing and the production of various cheese types Written for laboratory technicians and researchers, students learning the protocols for LAB isolation and characterisation, Microbiology in Dairy Processing is the authoritative reference for professionals and students.
Alexander Lerch An Introduction to Audio Content Analysis. Applications in Signal Processing and Music Informatics Alexander Lerch An Introduction to Audio Content Analysis. Applications in Signal Processing and Music Informatics Новинка

Alexander Lerch An Introduction to Audio Content Analysis. Applications in Signal Processing and Music Informatics

10498.58 руб.
With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included. Please visit the companion website: www.AudioContentAnalysis.org
Hannu Oja Robust Correlation. Theory and Applications Hannu Oja Robust Correlation. Theory and Applications Новинка

Hannu Oja Robust Correlation. Theory and Applications

6658.7 руб.
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.
Stephen Sangwine J. Quaternion Fourier Transforms for Signal and Image Processing Stephen Sangwine J. Quaternion Fourier Transforms for Signal and Image Processing Новинка

Stephen Sangwine J. Quaternion Fourier Transforms for Signal and Image Processing

5848.42 руб.
Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a central component of processing color images and complex valued signals. The book’s attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.

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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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