A Hybrid Genetic Algorithm for the Design of IIR Digital Filters

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.