Автор: Candy Название: Bayesian Signal Processing: Classical, Modern and Particle Filtering Methods ISBN: 0470180943 ISBN-13(EAN): 9780470180945 Издательство: Wiley Рейтинг: Цена: 119330.00 T Наличие на складе: Поставка под заказ. Описание: This book presents a unique viewpoint of signal processing from the Bayesian perspective in contrast to the pure statistical approach found in many textbooks. It features the next generation of processors that have recently been enabled with the advent of high speed/high throughput computers. The emphasis is on nonlinear/non-Gaussian problems, but classical techniques are included as special cases to enable the reader familiar with such methods to draw a parallel between the approaches. The common ground is the model sets. This text brings the reader from the classical methods of model-based signal processing including Kalman filtering for linear, linearized and approximate nonlinear processors as well as the recently developed unscented or sigma-point filters to the next generation of processors that will clearly dominate the future of model-based signal processing for years to come. Current applications (e.g. structures, tracking, equalization, biomedical) and simple examples to motivate the organization of the text are discussed. Examples are given to motivate all of the models and prepare the reader for further developments in subsequent chapters. In each case the processor along with accompanying simulations are discussed and applied to various data sets demonstrating the applicability and power of the Bayesian approach. The proposed text will be linked to the MATLAB (signal processing standard software) software package providing Notes as well as simple coding examples for illustrative purposes.
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(R) 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.
Автор: Paulo S. R. Diniz Название: Adaptive Filtering ISBN: 3030290565 ISBN-13(EAN): 9783030290566 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Невозможна поставка. Описание: The book provides a concise background on adaptive filtering, including the family of LMS, affine projection, RLS, set-membership algorithms and Kalman filters, as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more.
Автор: Poularikas, Alexander D. Название: Discrete Random Signal Processing and Filtering Primer with MATLAB ISBN: 0367386313 ISBN-13(EAN): 9780367386313 Издательство: Taylor&Francis Рейтинг: Цена: 67360.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB(R) problem-solving approaches and the very latest in discrete random signal processing and filtering. Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful Review Written for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offers a solid review of recent developments in discrete signal processing. The book also details the latest progress in the revolutionary MATLAB language. A Practical Self-Tutorial That Transcends Theory The author introduces an incremental discussion of signal processing and filtering, and presents several new methods that can be used for a more dynamic analysis of random digital signals with both linear and non-linear filtering. Ideal as a self-tutorial, this book includes numerous examples and functions, which can be used to select parameters, perform simulations, and analyze results. This concise guide encourages readers to use MATLAB functions - and those new ones introduced as Book MATLAB Functions - to substitute many different combinations of parameters, giving them a firm grasp of how much each parameter affects results. Much more than a simple review of theory, this book emphasizes problem solving and result analysis, enabling readers to take a hands-on approach to advance their own understanding of MATLAB and the way it is used within signal processing and filtering.
Автор: Rong Zheng; Cunqing Hua Название: Sequential Learning and Decision-Making in Wireless Resource Management ISBN: 3319505017 ISBN-13(EAN): 9783319505015 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book lays out the theoretical foundation of the so-called multi-armed bandit (MAB) problems and puts it in the context of resource management in wireless networks.
Автор: Mahmoud, Magdi S. , Xia, Yuanqing Название: Networked Filtering and Fusion in Wireless Sensor Networks ISBN: 1138374938 ISBN-13(EAN): 9781138374935 Издательство: Taylor&Francis Рейтинг: Цена: 63280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems. Examining the state of the art in information fusion, it covers the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks. After reading the book, readers will understand how to model parts of dynamic systems and use those models to develop distributed fusion control algorithms based on feedback control theory.
Автор: Zia Ur Rahman Название: Adaptive Filtering: Principles, Concepts and Applications ISBN: 1536147834 ISBN-13(EAN): 9781536147834 Издательство: Nova Science Рейтинг: Цена: 149940.00 T Наличие на складе: Невозможна поставка. Описание: This book titled Adaptive Filtering: Principles, Concepts and Applications covers principles, concepts and applications of adaptive filtering. The development of adaptive filtering started in 1976 and widely developed over different application areas. It is certainly not our ambition to cover everything of adaptive filtering principles and applications. Rather, this edited book features the latest methodological, technical and practical progress on promoting the successful use of adaptive filtering principles and applications, which are more useful in the current day scenario. The book contains ten chapters contributed by the experts in the area of adaptive filtering throughout the world. The various applications addressed are MIMO receivers, adaptive exon prediction for DNA analysis, beam steering for smart antennas for mobile applications, telecardiology systems, physiological signal analysis, brain computer interface applications, speech signal conditioning, filtering thoracic electrical bio-impedance, and inter symbol interference cancellation in wireless communication systems. The intended audience of this book will mainly consist of researchers, research students and practitioners in adaptive filtering and applications. The book is also of interest to researchers and industrial practitioners in areas such as algorithm developers, biomedical engineering, biomedical instrumentation, VLSI circuits design, and embedded systems. This edited book will present research outcomes on theoretical and technical issues related to real time applications.
Автор: JOSE APOLINARIO JR Название: QRD-RLS Adaptive Filtering ISBN: 1441935266 ISBN-13(EAN): 9781441935267 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides tools and knowledge in a simple way so that the reader is able to implement a particular QRD-RLS algorithm tailored for the application at hand. The book comprehensively compiles the research of more than a decade into a single publication.
Автор: Narayan Kovvali, Mahesh Banavar, Andreas Spanias Название: An Introduction to Kalman Filtering with MATLAB Examples ISBN: 1627051392 ISBN-13(EAN): 9781627051392 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 41580.00 T Наличие на складе: Невозможна поставка. Описание: The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications. This book presents a brief introduction to Kalman filtering.
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