Synopses & Reviews
Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, presents basic concepts of adaptive signal processing and filtering in a concise and straightforward manner. It concentrates on on-line algorithms whose adaptation occurs whenever a new sample of each environment signal is available. The material also illustrates block algorithms using a sub-band filtering framework whose adaptation occurs when a new block of data is available. Highlights of the new edition include: Expanded treatment of complex algorithms throughout the book New chapters on Data-Selective and Blind Adaptive Filtering An enlarged discussion of linear-constrained Wiener filters Detailed analysis of the affine projection algorithm Updated derivations and many new examples A primer on Kalman filtering in Appendix D as a complement to RLS algorithms. Algorithms are presented in a unified framework using a consistent notation that facilitates their actual implementation. The main algorithms are summarized and described in tables. Many examples address problems drawn from actual applications. The family of LMS and RLS algorithms as well as set-membership, sub-band, blind, nonlinear and IIR adaptive filtering, are covered. Problems are included at the end of chapters. Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, is intended for advanced undergraduate and graduate students studying adaptive filtering and will also serve as an up-to-date and useful reference for professional engineers working in the field.
Review
From the reviews of the third edition: "This text concentrates on studying on-line algorithms, those whose adaptation occurs whenever a new sample of each environment signal is available. ... This edition also includes basic introductions to nonlinear adaptive filtering and blind signal processing as natural extensions of the algorithms ... . The book is of great importance for digital signal processing undergraduate and graduate courses in universities." (George S. Stavrakakis, Zentralblatt MATH, Vol. 1155, 2009) "The book titled 'Adaptive Filtering: Algorithms and Practical Implementation,' Third Edition, by Paulo S. R. Diniz replaces two previous editions. This new edition has improved significantly upon those two editions. ... The book is also very practical. To attest to its suitability as a teaching text, the author has given a number of carefully developed examples which are useful ... to students. ... Overall, the book is excellent for teaching the subject of adaptive signal processing and enhances the landscape of textbooks on the subject." (Tokunbo Ogunfunmi, IEEE Communications Magazine, October, 2009)
Synopsis
This concise reference and textbook on adaptive filtering covers as many algorithms as possible while avoiding adapting notations and derivations related to the different algorithms. Another objective is to point out and concentrate on the algorithms that really work in actual applications. A Solutions Manual for the end-of-chapter problems is available to instructors. Also available, upon request to the author, is a set of master transparencies as well as a MATLAB Package including the MATLAB codes for all the algorithms described in the text. This book could be accompanied by a CD including the ancillary material for instructors and/or students. The author also has a Webpage for the book.
Synopsis
This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes adaptive filtering algorithms are presented in a unifed framework using clear notations that facilitate actual implementation. The main algorithms are described in tables which are detailed enough to allow the reader to verify the learned concepts. Many examples address problems drawn from actual applications. This book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. Several problems are included at the end of chapters and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test all of the algorithms in a fast manner. Additionally, the book provides easy access to working algorithms for practicing engineers.
Provided for instructors is a set of master transparencies as well as a MATLAB Package including the MATLAB codes for all the algorithms described in the text. The book is accompanied by a CD including the ancillary material for instructors and/or students. The author also has a webpage for the book.
Synopsis
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.
Synopsis
This book presents basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. Includes a CD supplement for instructors and students, offering lecture transparencies as well as MATLAB codes for all algorithms described in the text.
Table of Contents
Introduction to Adaptive Filtering.- Fundamentals of Adaptive Filtering.- The Least-Mean-Square (LMS) Algorithm.- LMS-Based Algorithms.- Conventional RLS Adaptive Filter.- Data-Selective Adaptive Filtering.- Adaptive Lattice-Based RLS Algorithms.- Fast Transversal RLS Algorithms.- QR-Decomposition-Based RLS Filters.- Adaptive IIR Filters.- Nonlinear Adaptive Filtering.- Subband Adaptive Filters.- Blind Adaptive Filtering.- Appendix A: Complex Differentiation.- Appendix B: Quantization Effects in the LMS Algorithm.- Appendix C: Quantization Effects in the RLS Algorithm.- Appendix D: Kalman Filters.