LMS and RLS adaptive L-filters

Author

Pitas, I. ; Venetsanoupoulos, A.N.

Author_Institution

Dept. of Electr. Eng., Thessaloniki Univ., Greece

fYear

1990

fDate

3-6 Apr 1990

Firstpage

1389

Abstract

An adaptive filter structure is proposed which is based on linear combinations of order statistics. An efficient method to update the filter coefficients is presented. It is based on the minimal mean-square-error criterion and is similar to the Widrow algorithm for linear adaptive filters. Another method for coefficient update that is similar to the RLS algorithm and has faster convergence properties is presented. The proposed filter can adapt well to a variety of noise probability distributions, including impulsive noise

Keywords

adaptive filters; convergence of numerical methods; filtering and prediction theory; least squares approximations; LMS adaptive L-filters; RLS adaptive L-filters; Widrow algorithm; coefficient update; convergence properties; impulsive noise; least mean square algorithm; linear combinations of order statistics; minimal mean-square-error criterion; noise probability distributions; recursive least squares algorithm; Adaptive filters; Adaptive signal processing; Convergence; Finite impulse response filter; Least squares approximation; Nonlinear filters; Probability distribution; Resonance light scattering; Signal processing; Statistics; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115647

Filename

115647