Design of FIR filter using PSO with CFA and inertia weight approach

An efficient method of digital finite impulse response filter design with linear phase using particle swarm optimization (PSO) with constriction factor (CFA) and inertia weight is presented in this paper. An iteration based technique is used to find the optimal solution of the objective function used in this paper. The objective function is the mean square error between the actual filter and the ideal filter. By using the optimization algorithm the deviation of the actual filter from the ideal filter is to be minimized. PSO with CFA and inertia weight approach uses a new equation to update the position and velocity of the particles according to iteration number. In this way particle moves towards the desired solution or optimal solution with in the search space. The simulation results are shown for the design of the filter and convergence behavior with respect to iteration cycle.