A comparison between Genetic Algorithm and PSO for linear phase FIR digital filter design

A comparative study between genetic algorithm and particle swarm optimization in FIR filter design is presented in this paper. FIR filter design involves multi-parameter optimization, on which the existing optimization algorithms donpsilat work efficiently. Given the filter specification to be designed, both algorithms generate a set of filter coefficients and try to meet the ideal frequency characteristic. For the problem at hand, the simulation of designing FIR filters have been done and the simulation results demonstrate that PSO is better than GA, not only in the convergence speed but also in the performance of the filter.