Application of a breeder genetic algorithm for system identification in an adaptive finite impulse response filter

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 then the genetic algorithm. For this reason we suggest using the genetic algorithm for off-line adaptation. Ay hybrid method combining the advantages of both methods is proposed for real world applications