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dc.contributor.authorDiker, Aykut
dc.contributor.authorAvci, Derya
dc.contributor.authorAvci, Engin
dc.contributor.authorGedikpinar, Mehmet
dc.date.accessioned16/12/21 12:07
dc.date.available16/12/21 12:07
dc.date.issued2019
dc.identifier.issn0030-4026
dc.identifier.urihttp://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10188
dc.identifier.urihttps://doi.org/10.1016/j.ijleo.2018.11.065
dc.description.abstractThe examination and classification of Electrocardiogram (ECG) records have become particularly significant for diagnosing heart diseases. Machine learning methods are widely used in classifying ECG signals. In this study, Physikalisch-Technische Bundesans
dc.language.isoEnglish
dc.publisherElsevıer Gmbh
dc.sourceOptık
dc.titleA new technique for ECG signal classification genetic algorithm Wavelet Kernel extreme learning machine
dc.typeArticle
dc.identifier.startpage46
dc.identifier.endpage55
dc.identifier.doi10.1016/j.ijleo.2018.11.065
dc.identifier.wosWOS:000462810600006
dc.identifier.volume180


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