Implementation of fractional order filters discretized by modified Fractional Order Darwinian Particle Swarm Optimization

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dc.authoridAlagoz, Baris Baykant/0000-0001-5238-6433
dc.authoridKavuran, Gurkan/0000-0003-2651-5005
dc.authoridATES, Abdullah/0000-0002-4236-6794
dc.authoridYeroglu, Celaleddin/0000-0002-6106-2374
dc.authorwosidAlagoz, Baris Baykant/ABG-8526-2020
dc.authorwosidKavuran, Gurkan/S-6935-2016
dc.authorwosidYeroglu, Celaleddin/ABG-9572-2020
dc.authorwosidATES, Abdullah/V-6929-2018
dc.contributor.authorAtes, Abdullah
dc.contributor.authorAlagoz, Baris Baykant
dc.contributor.authorKavuran, Gurkan
dc.contributor.authorYeroglu, Celaleddin
dc.date.accessioned2024-08-04T20:43:10Z
dc.date.available2024-08-04T20:43:10Z
dc.date.issued2017
dc.departmentİnönü Üniversitesien_US
dc.description.abstractDigital systems are placed at the core of information technology and they are used extensively in electronics. The digital filter realization has become a central topic of signal processing studies. This paper presents a discrete IIR filter design method for approximate realization of fractional order continuous filters in digital systems. For this purpose, Fractional Order Darwinian Particle Swarm Optimization (FODPSO) method is modified to provide better fitting of a discrete IIR filter function to a fractional order continuous filter and we implemented a hybrid version of FODPSO method, where the initial particle generation is carried out by arithmetical candidate point selection technique of the Base Optimization Algorithm (BaOA). This modification expands the search range of the FODPSO and thus the optimized discrete IIR filter can provide better approximation to amplitude response of fractional order continuous filter functions. In the paper, several illustrative examples are presented to demonstrate the performance of proposed methods. (C) 2017 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [215E261]en_US
dc.description.sponsorshipThis study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) with 215E261 project number.en_US
dc.identifier.doi10.1016/j.measurement.2017.05.017
dc.identifier.endpage164en_US
dc.identifier.issn0263-2241
dc.identifier.issn1873-412X
dc.identifier.scopus2-s2.0-85019430739en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage153en_US
dc.identifier.urihttps://doi.org/10.1016/j.measurement.2017.05.017
dc.identifier.urihttps://hdl.handle.net/11616/97823
dc.identifier.volume107en_US
dc.identifier.wosWOS:000403519500015en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofMeasurementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFractional order filteren_US
dc.subjectDiscrete realizationen_US
dc.subjectOptimizationen_US
dc.subjectParticle swarmen_US
dc.titleImplementation of fractional order filters discretized by modified Fractional Order Darwinian Particle Swarm Optimizationen_US
dc.typeArticleen_US

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