Least-Mean-Square Adaptive Filters

✍ Scribed by Simon Haykin (ed.), Bernard Widrow (ed.)

Publisher: Wiley
Year: 2003
Tongue: English
Leaves: 502
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Chapter 1 On the Efficiency of Adaptive Algorithms (pages 1–34): Bernard Widrow and Max Kamenetsky
Chapter 2 Traveling?Wave Model of Long LMS Filters (pages 35–78): Hans J. Butterweck
Chapter 3 Energy Conservation and the Learning Ability of LMS Adaptive Filters (pages 79–104): Ali H. Sayed and Vitor H. Nascimento
Chapter 4 On the Robustness of LMS Filters (pages 105–144): Babak Hassibi
Chapter 5 Dimension Analysis for Least?Mean?Square Algorithms (pages 145–173): Iven M.Y. Mareels, John Homer and Robert R. Bitmead
Chapter 6 Control of LMS?Type Adaptive Filters (pages 175–240): Prof. Dr.?Ing. Eberhard Hansler and Gerhard Uwe Schmidt
Chapter 7 Affine Projection Algorithms (pages 241–291): Steven L. Gay
Chapter 8 Proportionate Adaptation: New Paradigms in Adaptive Filters (pages 293–334): Zhe Chen, Steven L. Gay and Simon Haykin
Chapter 9 Steady?State Dynamic Weight Behavior in (N)LMS Adaptive Filters (pages 335–443): A. A. (Louis) Beex and James R. Zeidler
Chapter 10 Error Whitening Wiener Filters: Theory and Algorithms (pages 445–489): Jose C. Principe, Yadunandana N. Rao and Deniz Erdogmus

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