Component value selection for analog active filter using particle swarm optimization

In this work, a PSO based component value selection method is proposed for analog active filter. PSO is an efficient intelligent evolutionary algorithm for solving optimization problems. The aim of this work is to minimize the total design error of a 4^th order Butterworth low pass active filter that would be realized with component values which are compatible with E12 series. PSO provides a maximally flat response in the pass band and achieves smaller design error compared with previous methods.