Constrained adaptive LMS L-filters

Author

Kotropoulos, C. ; Pitas, I.

Author_Institution

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

fYear

1991

fDate

14-17 Apr 1991

Firstpage

1665

Abstract

Two novel adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics. These adaptive schemes are modifications of the standard LMS (least mean square) algorithm and have the ability to incorporate constraints imposed on coefficients in order to permit location invariant and unbiased estimation of a constant signal in the presence of additive white noise. The convergence properties of the proposed filters are considered. Both of them can adapt well to a variety of noise probability distributions ranging from short-tailed to long-tailed ones. Simulation examples are given

Keywords

adaptive filters; filtering and prediction theory; least squares approximations; probability; white noise; LMS algorithm; adaptive nonlinear filter structures; additive white noise; constrained adaptive LMS L-filters; convergence properties; least mean square; location invariant estimation; noise probability distributions; order statistics; simulation; Adaptive filters; Adaptive signal processing; Additive white noise; Convergence; Least squares approximation; Nonlinear filters; Probability distribution; Signal processing algorithms; Statistics; Sufficient conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.150604

Filename

150604