A Breeder Genetic Algorithm for Finite Impulse Filter Optimization

Oscar Montiel, Oscar Castillo, Patricia Melin, Roberto Sepúlveda

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

Abstract

We describe in this paper the application of a breeder genetic algorithm to the problem of parameter identification for an adaptive finite impulse filter. A breeder genetic algorithm was needed due to the epistiasis phenomena, which is present for this type of adaptive filter. The results of the genetic algorithm were compared to the traditional statistical method and, we found that the breeder genetic algorithm was clearly superior in most of the cases. However, the statistical Least Mean Squares method is faster than the genetic algorithm. For this reason we suggest using the genetic algorithm for off-line applications, and the statistical method for on-line adaptation.

Original languageEnglish
Title of host publicationProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
EditorsJ.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar
Pages582-585
Number of pages4
StatePublished - 2002
EventProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, United States
Duration: 8 Mar 200213 Mar 2002

Publication series

NameProceedings of the Joint Conference on Information Sciences
Volume6

Conference

ConferenceProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
Country/TerritoryUnited States
CityResearch Triange Park, NC
Period8/03/0213/03/02

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