Adaptive filter theory / Simon Haykin.

By: Haykin, Simon S, 1931-Material type: Text

TextLanguage: English Publication details: Upper Saddle River, N.J. : Prentice Hall, c2002. Edition: 4th edDescription: xvi, 920 p. : ill. ; 24 cmISBN: 0130901261; 9780130484345Subject(s): Adaptive filtersDDC classification: 621.3815324 LOC classification: TK7872.F5 | H368 2002Online resources: WorldCat details

Contents:

TOC Stochastic processes and models -- Wiener filters -- Linear prediction -- Method of steepest descent -- Least-mean-square adaptive filters -- Normalized least-mean-square adaptive filters -- Frequency-domain and subband adaptive filters -- Method of least squares -- Recursive least-squares adaptive filters -- Kalman filters -- Square-root adaptive filters -- Order-recursive adaptive filters -- Finite-precision effects -- Tracking of time-varying systems -- Adaptive filters using infinite-duration impulse response structures -- Blind deconvolution -- Back-propagation learning.

Summary: Summary: For courses in Adaptive Filters. This book examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons.

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Text	Dr. S. R. Lasker Library, EWU Reserve Section	Non-fiction	621.3815324 HAA (Browse shelf(Opens below))	C-1	Not For Loan	16610
Text	Dr. S. R. Lasker Library, EWU Reserve Section	Non-fiction	621.3815324 HAA (Browse shelf(Opens below))	C-2	Not For Loan	16611
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	621.3815324 HAA (Browse shelf(Opens below))	C-3	Available	17285
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	621.3815324 HAA (Browse shelf(Opens below))	C-4	Available	17286
Text	Dr. S. R. Lasker Library, EWU Circulation Section	Non-fiction	621.3815324 HAA (Browse shelf(Opens below))	C-5	Available	17287

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Includes bibliographical references (p. 870-911) and index.

TOC Stochastic processes and models --
Wiener filters --
Linear prediction --
Method of steepest descent --
Least-mean-square adaptive filters --
Normalized least-mean-square adaptive filters --
Frequency-domain and subband adaptive filters --
Method of least squares --
Recursive least-squares adaptive filters --
Kalman filters --
Square-root adaptive filters --
Order-recursive adaptive filters --
Finite-precision effects --
Tracking of time-varying systems --
Adaptive filters using infinite-duration impulse response structures --
Blind deconvolution --
Back-propagation learning.

Summary:
For courses in Adaptive Filters. This book examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons.

EEE

Tahur Ahmed

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