Fundamentals of Adaptive Filtering

Ali H. Sayed

  • 出版商: Wiley-IEEE Press
  • 出版日期: 2003-06-13
  • 售價: $2,200
  • 貴賓價: 9.8$2,156
  • 語言: 英文
  • 頁數: 1168
  • 裝訂: Hardcover
  • ISBN: 0471461261
  • ISBN-13: 9780471461265





The most comprehensive treatment of adaptive filtering available

Here is a fresh, broad, and systematic treatment of adaptive filtering, a subject of immense practical and theoretical value. The author illustrates extensive commonalities that exist among different classes of adaptive algorithms and even among different filtering theories. He also provides a uniform treatment of the subject matter, addressing some existing limitations, providing additional insights, and detailing extensions of current theory.

The book is designed to be self-contained, with careful attention given to appendices, problems, examples, and a variety of practical computer projects. The bibliography is up-to-date with extensive commentaries on how the contributions relate to each other in time and in context.

Each chapter includes concepts that reinforce the principles covered, bibliographic notes for further study, numerous problems that vary in difficulty and applications, computer projects that illustrate real-life applications, and helpful appendices.

MATLAB programs that solve all projects are available for download by all readers from the publisher’s Web site at The computer projects feature topics such as linear and decision-feedback equalization, channel estimation, beamforming, tracking of fading channels, line and acoustic echo cancellation, active noise control, OFDM receivers, CDMA receivers, and even finite-precision effects.

A complete solutions manual for all problems in the book is available to instructors upon request.

To gain insight into this vast and fast-moving field, you need a resource that is logically organized, specific in its presentation of each topic, and far-reaching in scope. Fundamentals of Adaptive Filtering is just that kind of resource.

Table of Contents





Optimal Estimation.

Linear Estimation.

Constrained Linear Estimation.

Steepest-Descent Algorithms.

Stochastic-Gradient Algorithms.

Steady-State Performance of Adaptive Filters.

Tracking Performance of Adaptive Filters.

Finite Precision Effects.

Transient Performance of Adaptive Filters.

Block Adaptive Filters.

The Least-Squares Criterion.

Recursive Least-Squares.

RLS Array Algorithms.

Fast Fixed-Order Filters.

Lattice Filters.

Laguerre Adaptive Filters.

Robust Adaptive Filters.


Author Index.

Subject Index.