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

Karaboga N., Cetinkaya B.

ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS, vol.3261, pp.482-488, 2004 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 3261
  • Publication Date: 2004
  • Journal Name: ADVANCES IN INFORMATION SYSTEMS, PROCEEDINGS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.482-488
  • Erciyes University Affiliated: Yes

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.