A variable step size algorithm using evolution strategies for adaptive filtering

Author

Ng, S.C. ; Chung, C.Y. ; Leung, S.H. ; Luk, A.

Author_Institution

Dept. of Comput. & Math., Hong Kong Inst. of Vocational Educ., Hong kong

Volume

1

fYear

1999

fDate

1999

Abstract

A new variable step size scheme for the least-mean-square (LMS) algorithm is proposed in this paper. The idea is basically a kind of evolutionary strategies. The step size candidates are generated and evaluated by calculating a square error measure based on a priori and a posteriori errors. The fittest candidate is selected for subsequent adaptation. The composition of the square error measure is regulated according to the mean square error so as to provide fast converging and tracking capability. The convergence performance is significantly improved and is less sensitive to eigenvalue spread

Keywords

adaptive signal processing; convergence of numerical methods; error analysis; evolutionary computation; filtering theory; least mean squares methods; a posteriori errors; a priori errors; adaptation; adaptive filtering; convergence performance; eigenvalue spread; evolutionary strategies; fast convergence; fast tracking; least-mean-square algorithm; square error measure; step size candidates; variable step size algorithm; Adaptive filters; Estimation error; Filtering algorithms; Finite impulse response filter; Information technology; Investments; Least squares approximation; Mathematics; Mean square error methods; Steady-state;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on

Conference_Location

Washington, DC

Print_ISBN

0-7803-5536-9

Type

conf

DOI

10.1109/CEC.1999.781980

Filename

781980