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Adaptive Filter Theory (Paperback)

by Simon Haykin (Author)

3.0 out of 5 stars See all reviews (2 customer reviews)

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Product details

Paperback: 936 pages
Publisher: Prentice Hall; 4 edition (12 Oct 2001)
Language English
ISBN-10: 0130901261
ISBN-13: 978-0130901262
Product Dimensions: 23.6 x 18.4 x 4 cm

Average Customer Review: 3.0 out of 5 stars See all reviews (2 customer reviews)

Amazon.co.uk Sales Rank: 203,812 in Books (See Bestsellers in Books)

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#12 in	Books > Science & Nature > Engineering & Technology > Electrical > Power Networks & Plants
#12 in	Books > Scientific, Technical & Medical > Engineering > Electrical Engineering > Power Networks, Stations & Plants
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Product Description

For courses in Adaptive Filters.

Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fourth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.

From the Back Cover

CONTENTS

Preface
Acknowledgments
Background and Preview

Chapter 1 Stochastic Processes and Models
Chapter 2 Wiener Filters
Chapter 3 Linear Prediction
Chapter 4 Method of Steepest Descent
Chapter 5 Least-Mean-Square Adaptive Filters
Chapter 6 Normalized Least-Mean-Square Adaptive Filters
Chapter 7 Frequency-Domain and Subband Adaptive Filters
Chapter 8 Method of Least Squares
Chapter 9 Recursive Least-Square Adaptive Filters
Chapter 10 Kalman Filters
Chapter 11 Square-Root Adaptive Filters
Chapter 12 Order-Recursive Adaptive Filters
Chapter 13 Finite-Precision Effects
Chapter 14 Tracking of Time-Varying Systems
Chapter 15 Adaptive Filters Using Infinite-Duration Impulse Response Structures
Chapter 16 Blind Deconvolution
Chapter 17 Back-Propagation Learning

Epilogue

Appendix A Complex Variables
Appendix B Differentiation with Respect to a Vector
Appendix C Method of Lagrange Multipliers
Appendix D Estimation Theory
Appendix E Eigenanalysis
Appendix F Rotations and Reflections
Appendix G Complex Wishart Distribution
Glossary

Bibliography

Index

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4 of 4 people found the following review helpful:

4.0 out of 5 stars An excellent text for the DSP researcher, 15 May 2001

By	balaji@ee.duke.edu (Duke Univ, NC, USA) - See all my reviews

This review is from: Adaptive Filter Theory (Prentice Hall Information & System Sciences Series) (Hardcover)

This is an excellent book which has been widely adopted around the world. The coverage is extensive and includes most of the modern techniques of Adaptive signal processing including Neural Networks etc. The organization of the text and the chapters is in a clear logical progression.

As a text book however I feel that it is perhaps too ambitious for a person new to the topic. I would have preferred lucidity of explanations over the depth of coverage for a text book of a course. My favourite book for this is still Woodrow and Wilson's classic text even though it is quite old and does not cover most new developments in the field.

However as a reference for those already somewhat aware of the topics, or for the serious DSP researcher, this book is an excellent resource which gives a very good review of most of the published material in the area.

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1 of 1 people found the following review helpful:

2.0 out of 5 stars Requires a good supporting cast, 10 Aug 2009

By	Mr. P. O'brien "paulob160" (Plymouth, England) - See all my reviews (REAL NAME)

This review is based on the Third Edition, a copy of which I have owned for some time now. I am a practising firmware/software engineer specialising in realtime control, DSP and datacoms, with pretensions to advanced techniques. I have a good grasp of matrix maths from reading Gilbert Strang's excellent texts but Prof. Haykin's book is too light on explanation and example to give much insight without considerable recourse to other material - the Matlab Signal Processing help files are good - and progress with his book is hard going. Of course trying to master difficult subjects with one text only is not really smart but in point of fact there aren't really ANY good pedagogical expositions in Adaptive Filters (see Sayed for example). I am trying Pedro Diniz' updated text now and it does look more promising as the supporting material is well developed. I have no doubt Prof. Haykin is masterful but could he have a little pity for us lesser mortals please.

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