Title :
Cooperative Coevolutionary Genetic Algorithm for Digital IIR Filter Design
Author :
Yu, Yang ; Xinjie, Yu
Author_Institution :
Tsinghua Univ., Beijing
fDate :
6/1/2007 12:00:00 AM
Abstract :
A novel algorithm for digital infinite-impulse response (IIR) filter design is proposed in this paper. The suggested algorithm is a kind of cooperative coevolutionary genetic algorithm. It considers the magnitude response and the phase response simultaneously and also tries to find the lowest filter order. The structure and the coefficients of the digital IIR filter are coded separately, and they evolve coordinately as two different species, i.e., the control species and the coefficient species. The nondominated sorting genetic algorithm-II is used for the control species to guide the algorithms toward three objectives simultaneously. The simulated annealing is used for the coefficient species to keep the diversity. These two strategies make the cooperative coevolutionary process work effectively. Comparisons with another genetic algorithm-based digital IIR filter design method by numerical experiments show that the suggested algorithm is effective and robust in digital IIR filter design
Keywords :
IIR filters; genetic algorithms; simulated annealing; sorting; coefficient species; control species; cooperative coevolutionary genetic algorithm; digital IIR filter; infinite-impulse response; magnitude response; nondominated sorting genetic algorithm-II; phase response; simulated annealing; Algorithm design and analysis; Chebyshev approximation; Design methodology; Digital filters; Genetic algorithms; IIR filters; Quantization; Robustness; Simulated annealing; Sorting; Coevolution; genetic algorithms (GAs); infinite-impulse response (IIR) digital filters; linear phase; lowest order;
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2007.893063