The Design of Digital IIR Filters Using a Differential Evolution Optimization Algorithm with Taguchi Crossover

Abstract

This paper presents a differential evolution algorithm that uses an elitist, ranking, random selection method and both two and three level Taguchi crossover. The algorithm is applied to 13 commonly used global numerical optimization test functions, including a spherical, three hyper-ellipsoid, the sum of different powers, Rastrigin's, Schwefel's, Griewank's, Rosen-brock's valley, Styblinski-Tang, Ackley's Path, Price-Rosenbrock, and Eggholder's functions. The algorithm is also used to design a number of optimal digital infinite impulse response (IIR) filters.