Title :
Application of improved genetic algorithm on IIR filter optimization
Author :
Ching-Hung Lee ; Yueh-Chang Tsai ; Chih-Min Lin
Author_Institution :
Dept. of Mech. Eng., Nat. Chung Hsing Univ., Taichung, Taiwan
Abstract :
This paper presents an improved GA which modified the GA based on allele gene adaptive mutation of mutation and crossover operation. There are three modified strategies to improve the performance of GA, elitist strategy is adopted to speed up convergence rate; the crossover operation is modified for effective searching; and the allele gene adaptive mutation exploits individuals´ allele gene in the population to maintain an appropriate level of diversity. Finally, simulation results of test function of optimization problems and IIR filter design are shown to illustrate the effectiveness and performance of the proposed improved GA.
Keywords :
IIR filters; adaptive systems; genetic algorithms; IIR filter design; allele gene adaptive mutation; convergence rate; crossover operation; elitist strategy; improved genetic algorithm; optimization problems; Abstracts; Optimization; Passband; Robustness; Sociology; Statistics; Genetic Algorithm; infinite-impulse-response (IIR) filter; optimization;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
DOI :
10.1109/ICMLC.2013.6890808