Stochastic analysis of the delayed LMS algorithm for a new model

Author

Tobias, Orlando J. ; Bermudez, José C M ; Bershad, Neil J.

Author_Institution

Dept. of Electr. Eng., Univ. Fed. de Santa Catarina, Florianopolis, Brazil

Volume

1

fYear

2000

fDate

2000

Firstpage

404

Abstract

This paper presents a stochastic analysis of the delayed least mean square (DLMS) adaptive algorithm using a new model. The new model does not use independence theory. Recursive difference equations are derived for the weight vector first and second moments. These equations yield new analytical results for the mean square error behavior. These results are compared to those of previous models. The new model is shown to be more general. The algorithm´s properties are explained that could not be explained using existing models. The theoretical behavior is in close agreement with Monte Carlo simulations for the cases studied. This provides support for the accuracy of the theoretical model

Keywords

adaptive signal processing; delay estimation; difference equations; least mean squares methods; numerical stability; recursive estimation; stochastic processes; Monte Carlo simulations; algorithm properties; convergence; correlated inputs; delayed LMS algorithm; delayed least mean square adaptive algorithm; first moment; imperfect delay estimates; mean square error behavior; new model; recursive difference equations; second moment; stability analysis; stochastic analysis; weight vector; Adaptive algorithm; Algorithm design and analysis; Delay estimation; Difference equations; Electronic mail; Least squares approximation; Mean square error methods; Stability; Stochastic processes; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.861991

Filename

861991