An efficient differential evolution with wavelet mutation algorithm for optimal IIR filter design

摘要

In this paper, an improved version of differential evolution (DE) algorithm which incorporates wavelet-based mutation strategy called differential evolution with wavelet mutation (DEWM) is proposed for the design of digital infinite impulse response (IIR) filters. Unlike fixed value of scaling factor in standard DE, the proposed optimisation technique DEWM adopts iteration dependent scaling factor governed by the wavelet function during the mutation process. This modification in the mutation process not only ensures the faster searching in the multidimensional search space but also the solution produced is very close to the global optimal solution. The effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA), conventional particle swarm optimisation (PSO) and standard DE with a superior DEWM-based outcome for the designed 8th order IIR low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters. Simulation results affirm that the proposed DEWM algorithm outperforms its counterparts not only in terms of quality output, i.e., sharpness at cut-off, pass band ripple and stop band attenuation but also in convergence speed with assured stability.