DocumentCode
1211683
Title
A stability result for RLS adaptive bilinear filters
Author
Lee, Junghsi ; Mathews, V.John
Author_Institution
Adv. Technol. Center, Ind. Technol. Res. Inst., Hsinchu, Taiwan
Volume
1
Issue
12
fYear
1994
Firstpage
191
Lastpage
193
Abstract
The article considers recursive least squares (RLS) adaptive nonlinear filtering using bilinear system models. It is shown that the extended RLS adaptive bilinear filter, as well as the equation-error RLS adaptive bilinear filter, are guaranteed to be stable in the sense that the time average of the squared estimation error is bounded whenever the underlying process that generates the input signals is stable in the same sense.<>
Keywords
adaptive filters; bilinear systems; filtering theory; least squares approximations; nonlinear filters; recursive filters; stability; RLS adaptive bilinear filters; adaptive nonlinear filtering; bilinear system models; equation-error RLS filter; extended RLS filter; input signals; recursive least squares; squared estimation error; stability; time average; Adaptive filters; Estimation error; Filtering; Least squares methods; Nonlinear equations; Nonlinear systems; Resonance light scattering; Signal generators; Signal processing; Stability;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.338749
Filename
338749
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