Application of a breeder genetic algorithm for finite impulse filter optimization

Authors:
Oscar Montiel;Oscar Castillo;Roberto Sepúlveda;Patricia Melin
Affiliations:
CITEDI, National Polytechnic Institute, Otay, Tijuana, Mexico;Department of Computer Science, Tijuana Institute of Technology, P.O. Box 4207, Chula Vista, CA;CITEDI, National Polytechnic Institute, Otay, Tijuana, Mexico;Department of Computer Science, Tijuana Institute of Technology, P.O. Box 4207, Chula Vista, CA
Venue:
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: FEA 2002
Year:
2004

Citing 7
Cited 3

Digital signal processing (3rd ed.): principles, algorithms, and applications

Digital signal processing (3rd ed.): principles, algorithms, and applications
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence

Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Digital Signal Processing: A Practical Approach

Digital Signal Processing: A Practical Approach
Digital Signal Processing Using MATLAB

Digital Signal Processing Using MATLAB
From Recombination of Genes to the Estimation of Distributions II. Continuous Parameters

PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Application Of A Breeder Genetic Algorithm For System Identification In An Adaptive Finite Impulse Response Filter

EH '01 Proceedings of the The 3rd NASA/DoD Workshop on Evolvable Hardware
A general class of nonlinear normalized adaptive filteringalgorithms

IEEE Transactions on Signal Processing

A self-adaptive migration model genetic algorithm for data mining applications

Information Sciences: an International Journal
Short Communication: Feedback linearization control of a two-link robot using a multi-crossover genetic algorithm

Expert Systems with Applications: An International Journal
An evaluation of differential evolution in software test data generation

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation

Quantified Score

Hi-index	0.01

Visualization

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. This 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 a multimodal space in most of the cases. However, the statistical least mean squares method is faster than the genetic algorithm. A hybrid method combining the advantages of both methods is proposed for real world applications.