Application of a breeder genetic algorithm for finite impulse filter optimization
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: FEA 2002
Application of a breeder genetic algorithm for filter optimization
Natural Computing: an international journal
Parameter identification of bilinear system based on genetic algorithm
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
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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 accuracy) 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. A hybrid method combining the advantages of both methods is proposed for real world applications.