PSO based optimized fractional derivative constraints for designing M-Channel filter bank

This article presents an efficient optimization algorithm for the design of M-Channel cosine modulated (CM) filter bank using polyphase components (PCs), fractional derivative constraints and particle swarm optimization (PSO). Sum of mean square error between the ideal and required response of prototype filter of CM bank is employed as a cost function for optimizing the PCs of prototype filter. Fractional derivative constraints are optimized using peak reconstruction error (PRE) of CM filter bank as a cost function using PSO. The efficiency of proposed method is investigated through various simulation results.