DocumentCode
1506332
Title
PWL nonlinear adaptive filter via RLS and NLMS algorithms
Author
Plaziac, Nathalie ; Chon Tam Ledinh ; Adoul, Jean-Pierre
Author_Institution
Dept. of Electr. Eng., Sherbrooke Univ., Que., Canada
Volume
45
Issue
5
fYear
1997
fDate
5/1/1997 12:00:00 AM
Firstpage
1364
Lastpage
1367
Abstract
The recursive least square (RLS) and the normalized least mean square (NLMS) algorithms are proposed for canonical piecewise linear (PWL) adaptive filters. The parameters are updated recursively in a manner similar to back-propagation. The simulation results indicate PWL adaptive filters can suitably model nonlinear systems
Keywords
adaptive filters; adaptive signal processing; filtering theory; least mean squares methods; least squares approximations; nonlinear filters; piecewise-linear techniques; recursive estimation; NLMS algorithm; PWL adaptive filters; RLS algorithm; back-propagation; canonical piecewise linear adaptive filters; nonlinear adaptive filter; normalized least mean square algorithm; recursive least square algorithm; simulation results; Adaptive filters; Least squares approximation; Least squares methods; Neural networks; Nonlinear filters; Piecewise linear approximation; Piecewise linear techniques; Resonance light scattering; Signal processing algorithms; Vectors;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.575711
Filename
575711
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