A Novel Approach for Optimal Digital FIR Filter Design Using Hybrid Grey Wolf and Cuckoo Search Optimization

Abstract

This paper represents designing of one-dimensional finite impulse filter (FIR) by computing the optimal filter coefficients in a way that the frequency response of the designed filter approximates ideal frequency response using proposed optimization algorithms. In this work, hybrid optimization of grey wolf and cuckoo search algorithm is considered to design a linear phase FIR low-pass, high-pass, band-pass and band-stop filters of 20th order. Analysis of simulation results of the designed filter is done, and various parameters are calculated such as maximum stopband ripple, maximum passband ripple and maximum attenuation in stop band. Results have been compared to recently published algorithms for optimization such as cat swarm optimization (CSO), particle swarm optimization (PSO), real-coded genetic algorithm (RCGA) and differential evolution (DE) to prove the superiority of the proposed algorithm.