Adaptive Filtering: Algorithms and Practical Implementation

by Paulo S. R. Diniz

Overview

In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified 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 covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes:

• Analytical and simulation examples in Chapters 4, 5, 6 and 10

• Appendix E, which summarizes the analysis of set-membership algorithm

• Updated problems and references

Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, 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 algorithms in a quick manner. Additionally, the book provides easy access to working algorithms for practicing engineers.

Product Details

ISBN-13:	9781461441052
Publisher:	Springer US
Publication date:	08/14/2012
Edition description:	4th ed. 2013
Pages:	652
Product dimensions:	6.00(w) x 9.20(h) x 1.60(d)

About the Author

Paulo S. R. Diniz his Ph.D. from Concordia University, Montreal, PQ, Canada, in 1984, all in electrical engineering. Since 1979, he has been with the undergraduate Department of Electronics and Computer Engineering at the UFRJ. He has also been with the graduate Program of Electrical Engineering at COPPE/UFRJ since 1984, where he is presently a Professor. He served as undergraduate course Coordinator and as Chairman of the graduate department. He is one of the three senior researchers and coordinators of the Brazilian National Excellence Center in Signal Processing. He has received the Rio de Janeiro State Scientist Award from the Governor of Rio de Janeiro State, and the Distinguished Research Scientist Award from COPPE/UFRJ (2002). From January 1991 to July 1992, he was a visiting Research Associate in the Department of Electrical and Computer Engineering of University of Victoria, Victoria, BC, Canada. In 2002 he served as Melchor Endowment Chair Professor in the Department of Electrical Engineering of the University of Notre Dame, Notre Dame, USA. He also holds a Docent position at the Signal Processing laboratory of Helsinki University of Technology, and has taught short courses at numerous institutions around the world. He has published over 200 refereed papers in some of these areas and wrote two books. He has received some awards for best papers and technical achievements. He was the Technical Program Chair of the 1995 MWSCAS held in Rio de Janeiro, Brazil. He has been on the technical committee of several international conferences including ISCAS, ICECS, EUSIPCO and MWSCAS. He has served Vice President for region 9 of the IEEE Circuits and Systems Society and as Chairman of the DSP technical committee of the same Society. He is also a Fellow of IEEE (for fundamental contributions to the design and implementation of fixed and adaptive filters and Electrical Engineering Education). He has served as associate editor for the following Journals: IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing from 1996 to 1999, IEEE Transactions on Signal Processing from 1999 to 2002, and the Circuits, Systems and Signal Processing Journal from 1998 to 2002. He was a distinguished lecturer of the IEEE Circuits and Systems Society for the years 2000 to 2001 and had served as distinguished lecturer of the IEEE Signal Processing Society in 2004.

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.

Editorial Reviews

A textbook for a graduate or undergraduate course in adaptive signal processing, for students with previous background in the basic principles of digital signal processing and stochastic processes. Focuses on describing a large number of algorithms rather than adapting notation and derivations, and shows how they work in a finite-precision implementation. Annotation c. by Book News, Inc., Portland, Or.

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