Sign-sign LMS convergence with independent stochastic inputs

Author

Dasgupta, Soura ; Johnson, Richard C., Jr. ; Baksho, Maylar A.

Author_Institution

Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA

Volume

36

Issue

1

fYear

1990

fDate

1/1/1990 12:00:00 AM

Firstpage

197

Lastpage

201

Abstract

The sign-sign adaptive least-mean-square (LMS) identifier filter is a computationally efficient variant of the LMS identifier filter. It involves the introduction of signum functions in the traditional LMS update term. Consideration is given to global convergence of parameter estimates offered by this algorithm, to a ball with radius proportional to the algorithm step size for white input sequences, specially from Gaussian and uniform distributions

Keywords

adaptive filters; convergence of numerical methods; filtering and prediction theory; least squares approximations; parameter estimation; stochastic processes; Gaussian distribution; LMS identifier filter; adaptive least mean square filter; algorithm step size; global convergence; independent stochastic inputs; parameter estimation; sign-sign identifier; uniform distributions; white input sequences; Adaptive filters; Convergence; Filtering algorithms; Image reconstruction; Least squares approximation; Parameter estimation; Pattern recognition; Robustness; Signal processing algorithms; Stochastic processes;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.50391

Filename

50391