Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7527
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dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:57:36Z-
dc.date.available2021-09-11T15:57:36Z-
dc.date.issued2009en_US
dc.identifier.issn0957-4174-
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2008.11.015-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7527-
dc.description.abstractThis paper presented the usage of statistics over the set of the features representing the electrocardiogram (ECG) signals. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of variabilities of the ECG signals. Four types of ECG beats (normal beat, congestive heart failure heat, ventricular tachyarrhythmia beat, atrial fibrillation beat) obtained from the Physiobank database were classified. The selected Lyapunov exponents, wavelet coefficients anti the power levels of power spectral density (PSD) values obtained by eigenvector methods of the ECG signals were used as inputs of the MLPNN trained with Levenberg-Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the variabilities of the ECG signals. (c) 2008 Elsevier Ltd. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectElectrocardiogram (ECG) signalsen_US
dc.subjectFeature extraction/selectionen_US
dc.subjectLyapunov exponentsen_US
dc.subjectWavelet coefficientsen_US
dc.subjectEigenvector methodsen_US
dc.titleStatistics Over Features of Ecg Signalsen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume36en_US
dc.identifier.issue5en_US
dc.identifier.startpage8758en_US
dc.identifier.endpage8767en_US
dc.identifier.wosWOS:000264782800005en_US
dc.identifier.scopus2-s2.0-60849087036en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.doi10.1016/j.eswa.2008.11.015-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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