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Least-Mean-Square Adaptive Filters

Simon Haykin (Editor), Bernard Widrow (Editor)
ISBN: 978-0-471-21570-7
512 pages
September 2003
Least-Mean-Square Adaptive Filters (0471215708) cover image


  • Edited by the original inventor of the technology.
  • Includes contributions by the foremost experts in the field.
  • The only book to cover these topics together.
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Table of Contents


Introduction (Simon Haykin).

1. On the Efficiency of Adaptive Algorithms (Berrnard Widrow and Max Kamenetsky).

2. Travelling-Wave Model of Long LMS Filters (Hans Butterweck).

3. Energy Conservation and the Learning Ability of LMS Adaptive Filters (Ali Sayed & Vitor H. Nascimento).

4. On the Robustness of LMS Filters (Babak Hassibi).

5. Dimension Analysis for Least-Mean-Square Algorithms (Iven M.Y. Mareels, et al.).

6. Control of LMS-Type Adaptive Filters (Eberhard Haensler and Gerhard Uwe Schmidt).

7. Affine Projection Algorithms (Steve Gay).

8. Proportionate Adaptation: New Paradigms in Adaptive Filters (Zhe Chen, et al.).

9. Steady-State Dynamic Weight Behavior in (N)LMS Adaptive Filters (A.A. (Louis) Beex and James R. Zeidler).

10. Error Whitening Wiener Filters: Theory and Algorithms (Jose Principe, et al.).


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Author Information

SIMON HAYKIN, PhD, is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.

BERNARD WIDROW, PhD, is Professor for Adaptive Systems at Stanford University.

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"...strongly recommended for researchers working in the field of signal processing and its applications." (IEEE Circuits & Devices, January/February 2006)
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