Convergence evaluation of a variable step-size LMSE adaptive switching algorithm

Shihab Jimaa, Tetsuya Shimamura, Hideki Takekawa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

A simple and robust variable step-size normalized switching adaptive algorithm is proposed here. The use of variable step-size in the adaptation process of Least Mean Switched Error (LMSE) algorithm (VSS-LMSE) is investigated. The switching algorithm consists of applying the Least Mean Fourth (LMF) algorithm and switching to the Least Mean Square (LMS) algorithm when the absolute value of error is greater than 1. The LMSE algorithm with a fixed step-size usually results in a trade-off between the residual error and the convergence speed of the algorithm. The VSS-LMSE algorithm presented here will eliminate much of this trade-off. In this paper the MSE of using the VSS-LMSF algorithm in the adaptation process of system identification over a dispersive channel is investigated. The step-size variation makes it possible for the VSS-LMSE algorithm to converge faster and to a lower steady state error than in the fixed step-size case. Moreover the proposed VSS-LMSE algorithm has a much lower steady state error than that in the case of VSS-NLMS algorithm.

Original languageBritish English
Title of host publicationProceedings - 2008 IEEE International Networking and Communications Conference, INCC 2008
PublisherIEEE Computer Society
Pages23-27
Number of pages5
ISBN (Print)9781424421510
DOIs
StatePublished - 1 May 2008
Event2008 IEEE International Networking and Communications Conference, INCC 2008 - Lahore, Pakistan
Duration: 1 May 20083 May 2008

Publication series

NameProceedings - 2008 IEEE International Networking and Communications Conference, INCC 2008

Conference

Conference2008 IEEE International Networking and Communications Conference, INCC 2008
Country/TerritoryPakistan
CityLahore
Period1/05/083/05/08

Keywords

  • Adaptive algorithms
  • LMSE
  • System identification

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