Estimating the optimal adaptation gain for the LMS algorithm

Author

Reason, Johnathan ; Wei Ren

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA

fYear

1993

fDate

15-17 Dec 1993

Firstpage

1587

Abstract

This paper evaluates two methods to see whether they are capable of estimating the optimal adaptation gain for the LMS algorithm in a stationary time-varying environment. The results show that the method of Kwong and Johnston (1992) runs counter to the goal of optimal trade-off between noise-rejection and tracking, while the method of Harris et al. (1986) (the VS method) comes closer to estimating the optimal adaptation gain, but there is much room for improvement-a preliminary improvement is suggested in the paper

Keywords

adaptive filters; identification; least squares approximations; noise; time-varying systems; tracking; LMS algorithm; noise-rejection; optimal adaptation gain; stationary time-varying environment; tracking; variable step method; Adaptive filters; Algorithm design and analysis; Counting circuits; Equations; Gain; Least squares approximation; Parameter estimation; System identification; Variable structure systems; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-1298-8

Type

conf

DOI

10.1109/CDC.1993.325445

Filename

325445

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2103522