Adaptive filters based on order statistics

Author

Pitas, I. ; Venetsanopoulos, A.N.

Author_Institution

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

Volume

39

Issue

2

fYear

1991

fDate

2/1/1991 12:00:00 AM

Firstpage

518

Lastpage

522

Abstract

An adaptive filter structure which is based on linear combinations of order statistics is proposed. An efficient method to update the filter coefficients is presented, which is based on the minimal mean-square error criterion and which is similar to the Widrow algorithm for the linear adaptive filters. Another method for coefficient update is presented, which is similar to the recursive least squares (RLS) algorithm and which has faster convergence properties. The proposed-filter can adapt well to a variety of noise probability distributions, including impulsive noise. It also performs well in the case of nonstationary signals and, therefore, it is suitable for image-processing applications

Keywords

adaptive filters; digital filters; filtering and prediction theory; picture processing; signal processing; RLS; Widrow algorithm; adaptive signal processing; coefficient update; faster convergence; filter coefficients; image-processing applications; impulsive noise; linear adaptive filters; minimal mean-square error criterion; noise probability distributions; nonstationary signals; order statistics; recursive least squares algorithm; Adaptive filters; Convergence; Finite impulse response filter; Image processing; Noise cancellation; Nonlinear filters; Probability distribution; Resonance light scattering; Signal processing; Statistics;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.80845

Filename

80845