An unbiased and cost-effective leaky-LMS filter

Author

Nascimento, Vitor H. ; Sayed, Ali H.

Author_Institution

Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA

fYear

1996

fDate

3-6 Nov. 1996

Firstpage

1078

Abstract

We propose a modified leaky-LMS filter that ensures stability of the estimates w(k) in the presence of bounded noise, without introducing any bias term and with the added cost of only a comparison and a multiplication per iteration when compared to the classical LMS algorithm. The new algorithm is further shown to converge for l/sub p/ noise and persistently exciting regressors. It also provides bounded estimates even in finite precision arithmetic. The stability and convergence properties of the new algorithm are established through a deterministic analysis that is based on the Lyapunov theory for the stability of nonlinear difference equations.

Keywords

adaptive filters; adaptive signal processing; digital arithmetic; filtering theory; least mean squares methods; numerical stability; LMS algorithm; Lyapunov theory; adaptive filter; bounded estimates; bounded noise; convergence properties; cost effective leaky LMS filter; deterministic analysis; finite precision arithmetic; modified leaky LMS filter; nonlinear difference equations stability; regressors; unbiased leaky LMS filter; Adaptive filters; Computational efficiency; Computational modeling; Convergence; Degradation; Difference equations; Fixed-point arithmetic; Least squares approximation; Stability; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-8186-7646-9

Type

conf

DOI

10.1109/ACSSC.1996.599109

Filename

599109