Title :
A Hybrid Genetic Algorithm for the Design of IIR Digital Filters
Author :
Ahmad, Sabbir U. ; Antoniou, Andreas
Author_Institution :
Victoria Univ., Victoria
Abstract :
A hybrid approach for the design of IIR filters using a genetic algorithm (GA) along with a quasi-Newton (QN) algorithm, referred to hereafter as the GQN algorithm is presented. The algorithm combines the flexibility and reliability inherent in the GA with the fast convergence and precision of the QN algorithm. The GA is used as a global search tool to explore different regions in the parameter space whereas the QN algorithm is used to exploit its efficiency in locating local solutions. The proposed algorithm involves a decimal encoding scheme and the optimization is carried out by minimizing an objective function based on the amplitude response error. Experimental results have shown that the proposed GQN algorithm can consistently achieve IIR filters that would satisfy arbitrary prescribed specifications.
Keywords :
IIR filters; Newton method; encoding; genetic algorithms; GQN algorithm; IIR digital filter; amplitude response error; decimal encoding; hybrid genetic algorithm; objective function minimization; optimization; quasiNewton algorithm; Algorithm design and analysis; Computer errors; Design optimization; Digital filters; Electronic mail; Encoding; Genetic algorithms; IIR filters; Optimization methods; Signal processing algorithms;
Conference_Titel :
Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
1-4244-1020-7
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2007.189