Performance comparison of genetic and differential evolution algorithms for digital FIR filter design

Authors:
Nurhan Karaboga;Bahadir Cetinkaya
Affiliations:
Department of Electronic Engineering, Erciyes University, Melikgazi, Kayseri, Turkey;Department of Electronic Engineering, Erciyes University, Melikgazi, Kayseri, Turkey
Venue:
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Year:
2004

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Abstract

Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum of a multi modal search space regardless of the initial parameter values, fast convergence, and using a few control parameters. DE algorithm which has been proposed particulary for numeric optimization problems is a population based algorithm like genetic algorithms using the similar operators; crossover, mutation and selection. In this work, DE algorithm has been applied to the design of digital Finite Impulse Response filters and compared its performance to that of genetic algorithm.