Download or read book Adaptive System Identification and Signal Processing Algorithms written by N. Kalouptsidis and published by . This book was released on 1993 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: An account of an important class of algorithmic families for adaptive system identification and signal processing. The LMS family and R&S and its fast versions, as well as the back propagation algorithms for neural networks, are examined in the context of algorithmic efficiency.
Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer Science & Business Media. This book was released on 2007-09-05 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Download or read book Adaptive Filtering written by Paulo S. R. Diniz and published by Springer Science & Business Media. This book was released on 2008-05-22 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, using clear notations that facilitate actual implementation. Important algorithms are described in detailed tables which allow the reader to verify learned concepts. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. The book is also supported by a web page maintained by the author.
Download or read book Adaptive Filtering written by Paulo Sergio Ramirez Diniz and published by Springer Science & Business Media. This book was released on 2002 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms. An instructor's manual, a set of master transparencies, and the MATLAB codes for all of the algorithms described in the text are also available. Useful to both professional researchers and students, the text includes 185 problems; over 38 examples, and over 130 illustrations. It is of primary interest to those working in signal processing, communications, and circuits and systems. It will also be of interest to those working in power systems, networks, learning systems, and intelligent systems.
Download or read book Adaptive Signal Processing written by Widrow and published by Pearson Education India. This book was released on 2016 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Subband Adaptive Filtering written by Kong-Aik Lee and published by John Wiley & Sons. This book was released on 2009-07-06 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. For beginners, the authors discuss the basic principles that underlie the design and implementation of subband adaptive filters. For advanced readers, a comprehensive coverage of recent developments, such as multiband tap–weight adaptation, delayless architectures, and filter–bank design methods for reducing band–edge effects are included. Several analysis techniques and complexity evaluation are also introduced in this book to provide better understanding of subband adaptive filtering. This book bridges the gaps between the mixed–domain natures of subband adaptive filtering techniques and provides enough depth to the material augmented by many MATLAB® functions and examples. Key Features: Acts as a timely introduction for researchers, graduate students and engineers who want to design and deploy subband adaptive filters in their research and applications. Bridges the gaps between two distinct domains: adaptive filter theory and multirate signal processing. Uses a practical approach through MATLAB®-based source programs on the accompanying CD. Includes more than 100 M-files, allowing readers to modify the code for different algorithms and applications and to gain more insight into the theory and concepts of subband adaptive filters. Subband Adaptive Filtering is aimed primarily at practicing engineers, as well as senior undergraduate and graduate students. It will also be of interest to researchers, technical managers, and computer scientists.
Download or read book Advanced Concepts in Adaptive Signal Processing written by W. Kenneth Jenkins and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although adaptive filtering and adaptive array processing began with research and development efforts in the late 1950's and early 1960's, it was not until the publication of the pioneering books by Honig and Messerschmitt in 1984 and Widrow and Stearns in 1985 that the field of adaptive signal processing began to emerge as a distinct discipline in its own right. Since 1984 many new books have been published on adaptive signal processing, which serve to define what we will refer to throughout this book as conventional adaptive signal processing. These books deal primarily with basic architectures and algorithms for adaptive filtering and adaptive array processing, with many of them emphasizing practical applications. Most of the existing textbooks on adaptive signal processing focus on finite impulse response (FIR) filter structures that are trained with strategies based on steepest descent optimization, or more precisely, the least mean square (LMS) approximation to steepest descent. While literally hundreds of archival research papers have been published that deal with more advanced adaptive filtering concepts, none of the current books attempt to treat these advanced concepts in a unified framework. The goal of this new book is to present a number of important, but not so well known, topics that currently exist scattered in the research literature. The book also documents some new results that have been conceived and developed through research conducted at the University of Illinois during the past five years.
Download or read book Optimal and Adaptive Signal Processing written by Peter M. Clarkson and published by Routledge. This book was released on 2017-11-01 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal and Adaptive Signal Processing covers the theory of optimal and adaptive signal processing using examples and computer simulations drawn from a wide range of applications, including speech and audio, communications, reflection seismology and sonar systems. The material is presented without a heavy reliance on mathematics and focuses on one-dimensional and array processing results, as well as a wide range of adaptive filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing. Optimal and Adaptive Signal Processing is a valuable guide for scientists and engineers, as well as an excellent text for senior undergraduate/graduate level students in electrical engineering.
Download or read book Adaptive Signal Processing Algorithms written by Victor Solo and published by . This book was released on 1995 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there has been considerable research activity in the theoretical study of ASP (and Adaptive Control) algorithms in recent years, most of the available literature has touched only briefly on performance analysis. This volume fills that gap by exploring the analysis of behavior (i.e., stability and performance) of Adaptive Signal Processing (ASP) algorithms -- discussing general methods of algorithm construction and general methods of algorithm analysis. Part I introduces ASP through its applications, shows how to construct ASP algorithms, and gives a detailed global stability and performance analysis in both deterministic and stochastic settings. Part II explores deterministic stability analysis by means of averaging methods, which are necessary to handle more complicated algorithms. Part III treats stochastic stability and performance by averaging methods. For practitioners and researchers in signal processing, communication and control.
Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer. This book was released on 2008-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Download or read book Learning Algorithms written by P. Mars and published by CRC Press. This book was released on 2018-01-18 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, interest in computational or non-symbolic artificial intelligence has grown. The algorithms involved have the ability to learn from past experience, and therefore have significant potential in the adaptive control of signals and systems. This book focuses on the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms, evolutionary strategies, and evolutionary programming. Hybrid combinations of various algorithms are also discussed.Chapter 1 provides a brief overview of the topics discussed and organization of the text. The first half of the book (Chapters 2 through 4) discusses the basic theory of the learning algorithms, with one chapter devoted to each type. In the second half (Chapters 5 through 7), the emphasis is on a wide range of applications drawn from adaptive signal processing, system identification, and adaptive control problems in telecommunication networks.Learning Algorithms: Theory and Applications in Signal Processing, Control and Communications is an excellent text for final year undergraduate and first year graduate students in engineering, computer science, and related areas. Professional engineers and everyone involved in the application of learning techniques in adaptive signal processing, control, and communications will find this text a valuable synthesis of theory and practical application of the most useful algorithms.
Download or read book Adaptive Signal Processing written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, a reference on the most relevant applications of adaptive filtering techniques. Top researchers in the field contributed chapters addressing applications in acoustics, speech, wireless and networking, where research is still very active and open.
Download or read book Adaptive Algorithms and Stochastic Approximations written by Albert Benveniste and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems. These diverse areas echo the classes of models which conveniently describe each corresponding system. Thus although there can hardly be a "general theory of adaptive systems" encompassing both the modelling task and the design of the adaptation procedure, nevertheless, these diverse issues have a major common component: namely the use of adaptive algorithms, also known as stochastic approximations in the mathematical statistics literature, that is to say the adaptation procedure (once all modelling problems have been resolved). The juxtaposition of these two expressions in the title reflects the ambition of the authors to produce a reference work, both for engineers who use these adaptive algorithms and for probabilists or statisticians who would like to study stochastic approximations in terms of problems arising from real applications. Hence the book is organised in two parts, the first one user-oriented, and the second providing the mathematical foundations to support the practice described in the first part. The book covers the topcis of convergence, convergence rate, permanent adaptation and tracking, change detection, and is illustrated by various realistic applications originating from these areas of applications.
Download or read book Adaptive Signal Processing written by Thomas S. Alexander and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The creation of the text really began in 1976 with the author being involved with a group of researchers at Stanford University and the Naval Ocean Systems Center, San Diego. At that time, adaptive techniques were more laboratory (and mental) curiosities than the accepted and pervasive categories of signal processing that they have become. Over the lasl 10 years, adaptive filters have become standard components in telephony, data communications, and signal detection and tracking systems. Their use and consumer acceptance will undoubtedly only increase in the future. The mathematical principles underlying adaptive signal processing were initially fascinating and were my first experience in seeing applied mathematics work for a paycheck. Since that time, the application of even more advanced mathematical techniques have kept the area of adaptive signal processing as exciting as those initial days. The text seeks to be a bridge between the open literature in the professional journals, which is usually quite concentrated, concise, and advanced, and the graduate classroom and research environment where underlying principles are often more important.
Download or read book Robust Adaptive Filtering Algorithms for System Identification and Array Signal Processing in Non Gaussian Environment written by Tiange Shao and published by . This book was released on 2011 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation proposes four new algorithms based on fractionally lower order statistics for adaptive filtering in a non-Gaussian interference environment. One is the affine projection sign algorithm (APSA) based on L1 norm minimization, which combines the ability of decorrelating colored input and suppressing divergence when an outlier occurs. The second one is the variable-step-size normalized sign algorithm (VSS-NSA), which adjusts its step size automatically by matching the L1 norm of the a posteriori error to that of noise. The third one adopts the same variable-step-size scheme but extends L1 minimization to Lp minimization and the variable step-size normalized fractionally lower-order moment (VSS-NFLOM) algorithms are generalized. Instead of variable step size, the variable order is another trial to facilitate adaptive algorithms where no a priori statistics are available, which leads to the variable-order least mean pth norm (VO-LMP) algorithm, as the fourth one. These algorithms are applied to system identification for impulsive interference suppression, echo cancelation [sic], and noise reduction. They are also applied to a phased array radar system with space-time adaptive processing (beamforming) to combat heavy-tailed non-Gaussian clutters. The proposed algorithms are tested by extensive computer simulations. The results demonstrate significant performance improvements in terms of convergence rate, steady-state error, computational simplicity, and robustness against impulsive noise and interference"--Abstract, leaf iv.
Download or read book Adaptive Signal Processing written by Bernard Widrow and published by Prentice Hall. This book was released on 1985 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and practical treatment of adaptive signal processing featuring frequent use of examples.
Download or read book Blind Equalization and System Identification written by Chong-Yung Chi and published by Springer Science & Business Media. This book was released on 2006-01-23 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: The absence of training signals from many kinds of transmission necessitates the widespread use of blind equalization and system identification. There have been many algorithms developed for these purposes, working with one- or two-dimensional signals and with single-input single-output or multiple-input multiple-output, real or complex systems. It is now time for a unified treatment of this subject, pointing out the common characteristics of these algorithms as well as learning from their different perspectives. "Blind Equalization and System Identification" provides such a unified treatment presenting theory, performance analysis, simulation, implementation and applications. This is a textbook for graduate courses in discrete-time random processes, statistical signal processing, and blind equalization and system identification. It contains material which will also interest researchers and engineers working in digital communications, source separation, speech processing, and other, similar applications.
