An atom search optimization approach for IIR system identification
dc.contributor.author | Ekinci, Serdar | |
dc.contributor.author | Budak, Cafer | |
dc.contributor.author | Izci, Davut | |
dc.contributor.author | Gider, Veysel | |
dc.date.accessioned | 2024-04-24T16:24:31Z | |
dc.date.available | 2024-04-24T16:24:31Z | |
dc.date.issued | 2023 | |
dc.department | Dicle Üniversitesi, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümü Koleksiyonu | en_US |
dc.description.abstract | Filtering, or digital signal processing, is a significant and fundamental requirement in fields such as signal systems and computers. The process of designing optimal digital filters is difficult, which has led researchers to design filters using emerging evolutionary computations. Metaheuristics have emerged as the most promising tool for solving optimization problems, with excellent development and improvement. However, it has not been clear how to select the best performing metaheuristic to design an optimal digital filter. In this paper, a digital infinite impulse response (IIR) filter is constructed using the atom search optimization (ASO) algorithm impressed by the physical motion of atoms in nature based on molecular dynamics. The simulation results obtained are extensively compared with the results of other optimization algorithms such as moth flame optimization, gravitational search algorithm and artificial bee colony optimization. ASO was found to have the highest percentage of improvement. Furthermore, eight cases are analyzed across four numerical filter instances with the same degree and four with reduced degree, and the results are validated by outperforming several different algorithm-based approaches in the literature. The stability analysis on the basis of pole zero diagrams further cements the efficacy of the ASO for IIR system identification problem. | en_US |
dc.identifier.citation | Ekinci, S., Budak, C., İzci, D. ve Gider, V. (2023). An atom search optimization approach for IIR system identification. International Journal of Modelling and Simulation, 1-17. | |
dc.identifier.doi | 10.1080/02286203.2023.2287968 | |
dc.identifier.issn | 0228-6203 | |
dc.identifier.issn | 1925-7082 | |
dc.identifier.scopus | 2-s2.0-85178180968 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://doi.org/10.1080/02286203.2023.2287968 | |
dc.identifier.uri | https://hdl.handle.net/11468/16751 | |
dc.identifier.wos | WOS:001120281400001 | |
dc.identifier.wosquality | N/A | |
dc.indekslendigikaynak | Web of Science | |
dc.indekslendigikaynak | Scopus | |
dc.language.iso | en | en_US |
dc.publisher | Taylor & Francis Inc | en_US |
dc.relation.ispartof | International Journal of Modelling and Simulation | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Digital Iir Filters | en_US |
dc.subject | Atom search optimization algorithm | en_US |
dc.subject | Metaheuristic algorithm | en_US |
dc.title | An atom search optimization approach for IIR system identification | en_US |
dc.title | An atom search optimization approach for IIR system identification | |
dc.type | Article | en_US |
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