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Neural Computing and Applications

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07-08-2021 | Original Article

Infinite impulse response system identification using average differential evolution algorithm with local search

Author: Burhanettin Durmuş

Published in: Neural Computing and Applications | Issue 1/2022

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Abstract

In this article, a new metaheuristic algorithm named average differential evolution with local search (ADE-LS) has been developed and implemented to find the optimal coefficients of unknown infinite impulse response (IIR) system as a system identifier. The developed method minimizes the error between unknown system output and the adaptive IIR filter output. Rapid convergence is aimed for the global solution in system identification problem using the ADE-LS based adaptive IIR filter modelling with local search. In this way, more precise prediction of filter coefficients is ensured in the filter design with multimodal error surface. ADE-LS algorithm is applied to four benchmarked IIR systems commonly studies in literature to show its performance. Results found by using ADE-LS are compared to other methods reported in terms of convergence rate and the mean square error value. The attained results approve the efficiency of the suggested method.

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Title: Infinite impulse response system identification using average differential evolution algorithm with local search
Author: Burhanettin Durmuş
Publication date: 07-08-2021
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 1/2022
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-021-06399-4

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