Performance Analysis of Optimal FIR LPF and HPF using AVOA

In this research work, the proposed metaheuristic technique so called African-vulture optimization algorithm (AVOA) has been adopted for designing digital low pass and high pass (LPF and HPF) filters. AVOA simulates the living habit and foraging behavior of African vultures. The living habit of the vultures is modeled using five main phases: population grouping, degree of hunger, exploration phase and exploitation phases. Since the evolutionary algorithms proved their dominance in many applications, AVOA has been deployed for finding required filter's coefficients. For designing these filters, linear phase symmetric filters of even order are best suited. Comparison has been made with the other pre-existing optimization techniques like particle swarm optimization(PSO), cuckoo search algorithm(CSA), hybrid grey-wolf and cuckoo search optimization(HGWOCS) and grey-wolf optimization(GWO) in terms of passband and stopband ripples (PBR and SBR), stopband attenuation (SBA), transition width (TW) and the results show that AVOA outperformed other algorithms.