Design of Optimal Active Low-Pass Filter by Hybrid Intensified Current Search

This paper proposes the optimal fourth-order Butterworth active low-pass filter design by the hybrid intensified current search (HICuS) algorithm. With AI-based modern optimization, the HICuS algorithm is one of the most efficient metaheuristic optimizers. The sum of squared error between the ideal characteristic curve and the actual characteristic curve of the fourth-order Butterworth active low-pass filter is set as the objective function to be minimized by the HICuS algorithm. Results obtained by the HICuS are compared with those obtained by the genetic algorithm (GA), artificial bee colony (ABC), particle swarm optimization (PSO) and ant colony optimization (ACO). As results, the fourth-order Butterworth active low-pass filter designed by the HICuS provides more optimal characteristic than other existing algorithms.