Linear phase low pass FIR filter design using Improved Particle Swarm Optimization

Abstract

In this paper, an optimal design of linear phase digital low pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO) has been presented. In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. An iterative method is introduced to find the optimal solution of FIR filter design problem. Genetic algorithm (GA), particle swarm optimization (PSO), improved particle swarm optimization (IPSO) has been used here for the design of linear phase low pass FIR filter. IPSO is an improved PSO that proposes a new definition for the velocity vector and swarm updating and hence the solution quality is improved. A comparison of simulation results reveals the optimization efficacy of the algorithm over the prevailing optimization techniques for the solution of the multimodal, non-differentiable, highly non-linear, and constrained filter design problems.