Measures of tracking performance for the LMS algorithm

Author

Hajivandi, M. ; Gardner, Willam A.

Author_Institution

Dept. of Electr. Eng., Tehran Polytech., Iran

Volume

38

Issue

11

fYear

1990

fDate

11/1/1990 12:00:00 AM

Firstpage

1953

Lastpage

1958

Abstract

Two measures of tracking performance for the LMS (least mean square) algorithm are compared and contrasted. These are the conventional time-average or temporal mean of the nonstationary mean-squared error (MSE) in excess of the minimum attainable MSE, and the novel temporal root-mean-squared value of the excess MSE, which takes into account the temporal variance as well as the temporal mean of the nonstationary MSE. These measures are evaluated for the LMS algorithm applied to two time-variant system identification problems, one involving a random Markov system and the other a periodic system. Optimal step-size parameters and minimum misadjustments are evaluated. It is shown that the conventional time-average performance measure is adequate only when the degree of nonstationarity is sufficiently low. For higher degrees of nonstationarity, the time-average performance measure can be misleading in studies of the tracking behavior of the LMS algorithm

Keywords

Markov processes; identification; least squares approximations; signal processing; time-varying systems; LMS algorithm; minimum misadjustments; periodic system; random Markov system; step-size parameters; time-variant system identification problems; tracking performance; Acoustics; Adaptive filters; Computer science; Fluctuations; Helium; Least squares approximation; Steady-state; Stochastic processes; Stochastic systems; System identification;

fLanguage

English

Journal_Title

Acoustics, Speech and Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

0096-3518

Type

jour

DOI

10.1109/29.103096

Filename

103096