A variable step size LMS algorithm

Author

Kwong, Raymond H. ; Johnston, Edward W.

Author_Institution

Dept. of Electr. Eng., Toronto Univ., Ont., Canada

Volume

40

Issue

7

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

1633

Lastpage

1642

Abstract

A least-mean-square (LMS) adaptive filter with a variable step size is introduced. The step size increases or decreases as the mean-square error increases or decreases, allowing the adaptive filter to track changes in the system as well as produce a small steady state error. The convergence and steady-state behavior of the algorithm are analyzed. The results reduce to well-known results when specialized to the constant-step-size case. Simulation results are presented to support the analysis and to compare the performance of the algorithm with the usual LMS algorithm and another variable-step-size algorithm. They show that its performance compares favorably with these existing algorithms

Keywords

adaptive filters; convergence of numerical methods; filtering and prediction theory; least squares approximations; adaptive filter; algorithm convergence; mean-square error; small steady state error; steady-state behavior; variable step size LMS algorithm; Adaptive filters; Algorithm design and analysis; Analytical models; Convergence; Equations; Least squares approximation; Performance analysis; Signal processing; Steady-state; System identification;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.143435

Filename

143435