Wavelet Neural Network for Classification of Bundle Branch Blocks

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dc.contributor.authorCeylan, Rahime
dc.contributor.authorOzbay, Yuksel
dc.date.accessioned2020-03-26T18:17:33Z
dc.date.available2020-03-26T18:17:33Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.descriptionWorld Congress on Engineering (WCE 2011) -- JUL 06-08, 2011 -- Imperial Coll, London, UNITED KINGDOMen_US
dc.description.abstractBundle branch blocks are very important for the heart treatment immediately. Left and right bundle branch blocks represent an independent predictor in which underlying cardiac disease that needs to be treated. In this study, we presented a model of wavelet neural network for classification of bundle branch blocks. The proposed wavelet neural network was implemented using Morlet and Mexican hat wavelet functions as activation function in hidden layer. ECG data in this study were formed by taken from MIT-BIH ECG Arrhythmia Database. Training and test data consist of three different beat types, which are belong to ECG signal classes of normal, right bundle branch block and left bundle branch block. The performed experimental studies were demonstrated that wavelet neural network designed by Mexican hat wavelet was successful than other network which designed by Morlet wavelet.en_US
dc.description.sponsorshipInt Assoc Engineers, IAENG, Soc Artificial Intelligence, IAENG, Soc Bioinformat, IAENG, Soc Computer Sci, IAENG, Soc Data Min, IAENG, Soc Elect Engn, IAENG, Soc Imagl Engn, IAENG, Soc Ind Engn, IAENG, Soc Informat Syst Engn, IAENG, Soc Internet Comput & Web Serv, IAENG, Soc Mech Engn, IAENG, Soc Operat Res, IAENG, Soc Sci Comput, IAENG, Soc Software Engn, IAENG, Soc Wireless Engnen_US
dc.description.sponsorshipCoordinatorship Selcuk University's Scientific Research Projectsen_US
dc.description.sponsorshipThis work was supported by the Coordinatorship Selcuk University's Scientific Research Projects.en_US
dc.identifier.endpage1007en_US
dc.identifier.isbn978-988-19251-4-5
dc.identifier.issn2078-0958en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1003en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/27047
dc.identifier.wosWOS:000393012800016en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherINT ASSOC ENGINEERS-IAENGen_US
dc.relation.ispartofWORLD CONGRESS ON ENGINEERING, WCE 2011, VOL IIen_US
dc.relation.ispartofseriesLecture Notes in Engineering and Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectWavelet neural networken_US
dc.subjectECGen_US
dc.subjectclassificationen_US
dc.subjectQRS detectionen_US
dc.titleWavelet Neural Network for Classification of Bundle Branch Blocksen_US
dc.typeConference Objecten_US

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