Analysis of the data-reusing LMS algorithm

Author

Roy, Sumit ; Shynk, John J.

Author_Institution

Dept. of Electr. Eng., Pennsylvania Univ., Philadelphia, PA, USA

fYear

1989

fDate

14-16 Aug 1989

Firstpage

1127

Abstract

A variant of the popular LMS (least mean square) algorithm, termed data-reusing LMS (DR-LMS) algorithms, is analyzed. This family of algorithms is parametrized by the number of reuses (L) of the weight update per data sample, and can be considered to have intermediate properties between the LMS and the normalized LMS algorithm. Analysis and experiments indicate faster convergence at the cost of reduced stability regions and additional computational complexity that is linear in the number of reuses

Keywords

computational complexity; convergence of numerical methods; least squares approximations; signal processing; stability; computational complexity; convergence; data-reusing LMS algorithm; least mean square; stability regions; weight update per data sample; Algorithm design and analysis; Computational complexity; Computational efficiency; Context; Convergence; Data analysis; Data communication; Least squares approximation; Signal processing algorithms; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/MWSCAS.1989.102053

Filename

102053

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1994697