A Breeder Genetic Algorithm for Finite Impulse Filter Optimization

Oscar Montiel, Oscar Castillo, Patricia Melin, Roberto Sepúlveda

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
EditoresJ.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar
Páginas582-585
Número de páginas4
EstadoPublicada - 2002
EventoProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, Estados Unidos
Duración: 8 mar. 200213 mar. 2002

Serie de la publicación

NombreProceedings of the Joint Conference on Information Sciences
Volumen6

Conferencia

ConferenciaProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
País/TerritorioEstados Unidos
CiudadResearch Triange Park, NC
Período8/03/0213/03/02

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