IIR filter optimization using improved chaotic harmony search algorithm

Abstract

Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, conventional derivative-based techniques fail when used in adaptive Filter design. In this sense, global optimization techniques are required in order to avoid local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently introduced population-based algorithm that has been successfully applied to global optimization problems. In the present paper, adaptive IIR filtering is formulated as a nonlinear optimization problem and then an improved version of HS incorporating chaotic search (CIHS) is introduced to solve the identification problem of three benchmark IIR systems. Furthermore, the performance of the proposed methodology is compared with HS and two well-known metaheuristic algorithms, genetic algorithm (GA) and particle swarm optimization (PSO) and a modified version of PSO called PSOW (Particle Swarm Optimization with weight Factor). The results demonstrate that the proposed method has superior performance over the other above-mentioned algorithms in terms of convergence speed and accuracy.

A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications

“…e design of adaptive infinite impulse response (IIR) filter system was optimized by Shafaati and Mojallali [37]. ey incorporated chaos in HSA to solve the identification problem of IIR system.…”

Penerapan Harmony Search Algorithm untuk Menyelesaikan Economic Dispatch dengan Memperhitungkan Rugi-Rugi Transmisi

“…Metode HSA ini ditemukan oleh Zong Woo Geem pada tahun 2001. Metode HSA ini merupakan metode yang terinspirasi dari nada-nada musik yang di dengar [10][11][12][13][14][15].…”

Design of Efficient Low Pass Infinite Impulse Response Filter Using Dynamic Regional Harmony Search Algorithm with Opposition and Local Learning and Comparison with Harmony Search Algorithm

“…An updated version technique is developed for the optimization of the IIR filter using the improved chaotic harmony search algorithm (Shafaati and Mojallali 2018) that has to work with more complexities in the real time operating applications and compared with HS, GA, PSO, PSOW. In any digital signal processing optimization of filters is most efficient.…”