Adaptive Filter Theory, International Edition (5e) : 9780273764083

Adaptive Filter Theory, International Edition (5e)

Published by
Pearson Higher Ed USA
Available on demand
Title type
Title type

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 fifth 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.

Table of contents
  • Chapter 1            Stochastic Processes and Models
  • Chapter 2            Wiener Filters
  • Chapter 3            Linear Prediction
  • Chapter 4            Method of Steepest Descent
  • Chapter 5            Method of Stochastic Gradient Descent
  • Chapter 6            The Least-Mean-Square (LMS) Algorithm
  • Chapter 7            Normalized Least-Mean-Square (LMS) Algorithm and Its Generalization
  • Chapter 8            Block-Adaptive Filters
  • Chapter 9            Method of Least Squares
  • Chapter 10            The Recursive Least-Squares (RLS) Algorithm
  • Chapter 11            Robustness
  • Chapter 12            Finite-Precision Effects
  • Chapter 13            Adaptation in Nonstationary Environments
  • Chapter 14            Kalman Filters
  • Chapter 15            Square-Root Adaptive Filters
  • Chapter 16            Order-Recursive Adaptive Filters
  • Chapter 17            Blind Deconvolution
New to this edition

  • Chapter 5  on the method Stochastic of gradient descent is new
  • Changes have been made to chapter 6 (the old chapter 5) on the LMS algorithm in light of the new  chapter 5.
  • The new chapter 11 on robustness is new.
  • Minor changes have been made to finite precision effects renumbered as Chapter 12.
  • Chapter 13 on Adaptation in Nonstationary environments , replacing the old chapter on Time varying systems, has been substantially changed to make room for new algorithms, IDBD and Autoptstep.
  • Minor changes have been made to Kalman filters positioned as new Chapter 14.
  • The chapter on Epilogue is brand new.
  • The appendix on differentiation in the complex domain has been completely revised using the Wirtinger calculus.
  • The appendix on the Langevin equation is brand new.
  • The Bibliography is completely updated.

Features & benefits
  • In-depth treatment of adaptive filters in a highly readable and understandable fashion.
  • Extensive use of illustrative examples.
  • Extensive use of MATLAB experiments—Illustrates the practical realities and intricacies of adaptive filters, the codes for which can be downloaded from the Web.
  • Extensive bibliography of the subject.
Author biography

Simon Haykin received his B.Sc. (First-class Honours), Ph.D., and D.Sc., all in Electrical Engineering from the University of Birmingham, England. He is a Fellow of the Royal Society of Canada, and a Fellow of the Institute of Electrical and Electronics Engineers. He is the recipient of the Henry Booker Gold Medal from URSI, 2002, the Honorary Degree of Doctor of Technical Sciences from ETH Zentrum, Zurich, Switzerland, 1999, and many other medals and prizes.

He is a pioneer in adaptive signal-processing with emphasis on applications in radar and communications, an area of research which has occupied much of his professional life.