A Multiobjective Genetic Algorithm for Asymmetric FIR Filters

A genetic algorithm (GA) for the design of asymmetric FIR filters that would satisfy multiple requirements imposed on the amplitude response and group-delay characteristic is proposed. The GA implements a multiobjective optimization approach for obtaining so-called Pareto-optimal solutions of the problem at hand. Flexibility is introduced in the design by imposing phase linearity only in the passband instead of the entire baseband as in conventional designs. The proposed GA is a specially tailored elitist nondominated sorting genetic algorithm (ENSGA) and it involves a decimal encoding scheme and a multiobjective error formulation based on the amplitude response and passband group delay. Experimental results show that the ENSGA leads to improved amplitude response as well as delay characteristic relative to those achieved by using a state-of-the-art weighted least-squares approach.