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Least-Mean-Square Adaptive Filters Hardcover – Sep 8 2003


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

From the Back Cover

A landmark text in LMS filter technology–– from thefield’s leading authorities

In the field of electrical engineering and signal processing,few algorithms have proven as adaptable as the least-mean-square(LMS) algorithm. Devised by Bernard Widrow and M. Hoff, this simpleyet effective algorithm now represents the cornerstone for thedesign of adaptive transversal (tapped-delay-line) filters.

Today, working efficiently with LMS adaptive filters not onlyinvolves understanding their fundamentals, it also means stayingcurrent with their many applications in practical systems. However,no single resource has presented an up-to-the-minute examination ofthese and all other essential aspects of LMS filters–untilnow.

Edited by Simon Haykin and Bernard Widrow, the original inventorof the technology, Least-Mean-Square Adaptive Filters offers themost definitive look at the LMS filter available anywhere. Here,readers will get a commanding perspective on the desirableproperties that have made LMS filters the turnkey technology foradaptive signal processing. Just as importantly, Least-Mean-SquareAdaptive Filters brings together the contributions of renownedexperts whose insights reflect the state-of-the-art of the fieldtoday. In each chapter, the book presents the latest thinking on awide range of vital, fast-emerging topics, including:

  • Traveling-wave analysis of long LMS filters
  • Energy conservation and the learning ability of LMS adaptivefilters
  • Robustness of LMS filters
  • Dimension analysis for LMS filters
  • Affine projection filters
  • Proportionate adaptation
  • Dynamic adaptation
  • Error whitening Wiener filters

As the editors point out, there is no direct mathematical theoryfor the stability and steady-state performance of the LMS filter.But it is possible to chart its behavior in a stationary andnonstationary environment. Least-Mean-Square Adaptive Filters putsthese defining characteristics into sharp focus, and–more thanany other source–brings you up to speed on everything that theLMS filter has to offer.


Inside This Book (Learn More)
First Sentence
The basic component of most adaptive filtering and signal processing systems is the adaptive linear combiner [1-5] shown in Figure 1.1. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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