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

被引:12
|
作者
Durmus, Burhanettin [1 ]
机构
[1] Kutahya Dumlupinar Univ, Dept Elect & Elect Engn, TR-43100 Kutahya, Turkey
来源
NEURAL COMPUTING & APPLICATIONS | 2022年 / 34卷 / 01期
关键词
Infinite impulse response filter; Metaheuristic algorithms; Optimization; System identification; PARTICLE SWARM OPTIMIZATION; BAT ALGORITHM; DESIGN METHOD; LMS;
D O I
10.1007/s00521-021-06399-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:375 / 390
页数:16
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