Particle Swarm Optimization Algorithm for Designing Optimal IIR Digital Filter

A particle swarm optimization (PSO) algorithm with constriction factor and inertia weight is applied for magnitude approximation of infinite impulse response (IIR) filter based on L1-approximation error criterion. The proposed particle swarm optimization algorithm, which is a population-based stochastic optimization technique enhances the search capability and provides a fast convergences for calculating the optimal filter coefficients. The filter designed based on L1-approximation error possesses flat passbands and stopbands while keeping the transition band comparable to that of the least square design. A comparison has been made with other design techniques, demonstrating that PSO with enhanced diversity and convergence gives better or at least comparable results or designing digital IIR filters than the existing genetic algorithm based methods.