A robust M-estimate adaptive filter for impulse noise suppression

Author

Zou, Yuexian ; Chan, S.C. ; Ng, T.S.

Author_Institution

Dept. of Electr. & Electron. Eng., Hong Kong Univ., Hong Kong

Volume

4

fYear

1999

fDate

15-19 Mar 1999

Firstpage

1765

Abstract

In this paper, a robust M-estimate adaptive filter for impulse noise suppression is proposed. The objective function used is based on a robust M-estimate. It has the ability to ignore or down weight large signal error when certain thresholds are exceeded. A systematic method for estimating such thresholds is also proposed. An advantage of the proposed method is that its solution is governed by a system of linear equations. Therefore, fast adaptation algorithms for traditional linear adaptive filters can be applied. In particular, a M-estimate recursive least square (M-RLS) adaptive algorithm is studied in detail. Simulation results show that it is more robust against individual and consecutive impulse noise than the MN-LMS and the N-RLS algorithms. It also has fast convergence speed and a low steady state error similar to its RLS counterpart

Keywords

adaptive estimation; adaptive filters; convergence of numerical methods; impulse noise; interference suppression; least squares approximations; recursive estimation; recursive filters; M-RLS adaptive algorithm; M-estimate recursive least square adaptive algorithm; convergence speed; fast adaptation algorithms; impulse noise suppression; linear equations; objective function; robust M-estimate adaptive filter; signal error; steady state error; systematic method; thresholds; Adaptive algorithm; Adaptive filters; Convergence; Equations; Filtering algorithms; Least squares approximation; Least squares methods; Noise robustness; Resonance light scattering; Steady-state;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.758261

Filename

758261