Publication:
A new intelligent decision making system combining classical methods, evolutionary algorithms and statistical techniques for optimal digital FIR filter design and their performance evaluation

dc.contributor.buuauthorKuyu, Yiğit Çağatay
dc.contributor.buuauthorVatansever, Fahri
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentElektrik Elektronik Mühendisliği Bölümü
dc.contributor.orcid0000-0002-7054-3102
dc.contributor.orcid0000-0002-3885-8622
dc.contributor.researcheridAAG-8425-2021
dc.contributor.researcheridAAC-6923-2021
dc.contributor.scopusid57191904606
dc.contributor.scopusid22636392600
dc.date.accessioned2023-04-05T12:11:02Z
dc.date.available2023-04-05T12:11:02Z
dc.date.issued2016-10-06
dc.description.abstractFiltering is one of the most important processes in electrical engineering. In digital systems, there are several methods that have been developed for filter designs. In this study, a new decision making system, which can be operated online or offline, based on statistical tests are developed for choosing the most appropriate FIR filter coefficients. For this purpose, this coefficients are optimized comparatively with nine evolutionary algorithms by using combination of some of fourteen windowing and four error functions(more than six hundred different combinations) as well as can be found via nine classical methods. As the evolutionary algorithms use random variables to achieve their results, they may not always make same design on each run. Therefore, this system is need to make a valid comparison between the algorithms employed. The key feature of proposed system is artificial intelligence,phase which sorts algorithms from best to worst under certain criteria according to chosen error function after using Kruskal-Wallis and multiple comparison tests. The proposed new approach in this intelligent decision making system, which can be also used for special, practical and educational purposes, gives the best results in between the algorithms for FIR filter design according to user requirements.
dc.identifier.citationKuyu, Y. Ç. ve Vatansever, F. (2016). "A new intelligent decision making system combining classical methods, evolutionary algorithms and statistical techniques for optimal digital FIR filter design and their performance evaluation". AEU - International Journal of Electronics and Communications, 70(12), 1651-1666.
dc.identifier.endpage1666
dc.identifier.issn1434-8411
dc.identifier.issn1618-0399
dc.identifier.issue12
dc.identifier.scopus2-s2.0-84994626932
dc.identifier.startpage1651
dc.identifier.urihttps://doi.org/10.1016/j.aeue.2016.10.004
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S143484111630930X
dc.identifier.urihttp://hdl.handle.net/11452/32202
dc.identifier.volume70
dc.identifier.wos000389098600011
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherElsevier
dc.relation.bapHDP(MH)-2016/19
dc.relation.journalAEU - International Journal of Electronics and Communications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectEngineering
dc.subjectTelecommunications
dc.subjectFilter design
dc.subjectEvolutionary algorithm
dc.subjectOptimization
dc.subjectArtificial intelligence
dc.subject.scopusIIR Filter; Impulse Response; Particle Swarm Optimization
dc.subject.wosEngineering, electrical & electronic
dc.subject.wosTelecommunications
dc.titleA new intelligent decision making system combining classical methods, evolutionary algorithms and statistical techniques for optimal digital FIR filter design and their performance evaluation
dc.typeArticle
dc.wos.quartileQ3 (Engineering, electrical & electronic)
dc.wos.quartileQ4 (Telecommunications)
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Elektrik Elektronik Mühendisliği Bölümü
local.indexed.atScopus
local.indexed.atWOS

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