Moth Flame Optimization Algorithm for Optimal FIR Filter Design

This paper presents the application of Moth Flame optimization (MFO) algorithm to determine best impulse response coefficients FIR low pass, high band pass and stop filters. MFO was inspired by observing navigation strategy moths in nature called transverse orientation composed three mathematical sub-models. The performance proposed technique compared those other well-known performing techniques like Particle Swarm Optimization (PSO), Novel (NPSO), Improved (INPSO), Genetic Algorithm (GA), Parks McClellan (PM) Algorithm. performances based designed optimized filters have proved be superior as obtained PSO, NPSO, INPSO, GA, PM Simulation results indicated that maximum ripples 0.057326, transition width 0.079 fitness value 1.3682 is better than Algorithms. or fluctuations at range which signals are attenuated very low. reduced rate a signal changes from either filter vice versa good. Also, small an indication values control variable near its optimum solutions. design this work generates excellent solution with computational efficiency. shows outstanding for design.