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.
Автор: K.J. Astr?m; G.C. Goodwin; P.R. Kumar Название: Adaptive Control, Filtering, and Signal Processing ISBN: 0387979883 ISBN-13(EAN): 9780387979885 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The area of adaptive systems encompasses recursive identification, adaptive control, filtering, and signal processing. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult.
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: Fredric J. Harris Название: Multirate Signal Processing for Communication Systems ISBN: 877022210X ISBN-13(EAN): 9788770222105 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Multirate Signal processing can improve system performance and reduce costs in applications ranging from laboratory instruments, cable modems, wireless systems, satellites, Radar, Sonar, and consumer entertainment products. This second edition continues to offer a systematic, clear, and intuitive introduction to multirate signal processing for working engineers and system designers. Significant new material and fresh concepts, including Green Signal Processing techniques have been introduced.
The author uses extensive examples and figures to illustrate a wide range of multirate techniques, from basic resampling to leading-edge cascade and multi-stage filter structures. Along the way he draws on extensive research and consulting experience to introduce processing “tricks” shown to maximize performance and efficiency. Coverage includes:
Effect of sampling and resampling in time and frequency domains.
Relationships between FIR filter specifications and filter length (# of taps).
Window design and equal-ripple (Remez) design techniques.
Square-Root Nyquist and Half-band Filters including new enhancements.
Polyphase FIR filters: up-sampling, down-sampling.
Polyphase M-path analysis and synthesis channelizers and cascade pairs.
Polyphase interpolators for arbitrary sample rate changes.
Описание: This book is devoted to the application of advanced signal processing on event-related potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive neuroscience.
Автор: Meyer, Fernand Название: Topographical tools for filtering and segmentation 1 ISBN: 1786301571 ISBN-13(EAN): 9781786301574 Издательство: Wiley Рейтинг: Цена: 22010.00 р. Наличие на складе: Поставка под заказ.
Описание:
Mathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools.
Volume 1 is devoted to watersheds. The topography of a graph appears by observing the evolution of a drop of water moving from node to node on a weighted graph, along flowing paths, until it reaches regional minima. The upstream nodes of a regional minimum constitute its catchment zone.
The catchment zones may be constructed independently of each other and locally, in contrast with the traditional approach where the catchment basins have to be constructed all at the same time. Catchment zones may overlap, and thus, a new segmentation paradigm is proposed in which catchment zones cover each other according to a priority order. The resulting partition may then be corrected, by local and parallel treatments, in order to achieve the desired precision.
Автор: Schilling Robert J Название: Digital Signal Processing Using MATLAB ISBN: 1305636600 ISBN-13(EAN): 9781305636606 Издательство: Cengage Learning Рейтинг: Цена: 10770.00 р. Наличие на складе: Нет в наличии.
Описание: Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB (R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter.
Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB (R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.
Автор: Principe Jose C Название: Kernel Adaptive Filtering ISBN: 0470447532 ISBN-13(EAN): 9780470447536 Издательство: Wiley Рейтинг: Цена: 16782.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: * On-line learning is a fundamental tool in adaptive signalprocessing * Presents on-line learning from a signal processingperspective.
Описание: Subband adaptive filtering is rapidly becoming one of the most effective techniques for reducing computational complexity and improving the convergence rate of algorithms in adaptive signal processing applications. This book provides an introductory, yet extensive guide on the theory of various subband adaptive filtering techniques.
Автор: Mark Nitzberg; David Mumford; Takahiro Shiota Название: Filtering, Segmentation and Depth ISBN: 3540564845 ISBN-13(EAN): 9783540564843 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of computer vision which addresses the low-level image processing issues of noise removal and smoothing, describes a robust contour tracing algorithm that produces a cartoon of the important lines in any image, and explains how to reconstruct the geometry of objects in a scene.
Описание: The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. There remains a need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. This book attempts to satisfy the above requirement. The algorithms are made clear using MATLAB programs.
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