SUPERVISED CLASSIFICATION OF ECG USING NEURAL NETWORKS

dc.contributor.authorBelgacem, Nen_US
dc.contributor.authorChikh, Maen_US
dc.contributor.authorBereksi Reguig, Fen_US
dc.date.accessioned2012-05-23T14:52:54Zen_US
dc.date.available2012-05-23T14:52:54Zen_US
dc.date.issued2003-09-27en_US
dc.descriptionConférence Internationale sur les Systèmes de Télécommunication , d’Electronique Médicale et d’Automatique, CISTEMA’2003en_US
dc.description.abstractIn this study, two kinds of neural networks are employed to develop a supervised ECG beat classifier. In order to improve the performance of the MLP classifier for application to ECG signal, the performance is compared to an LVQ neural network classifier. The two classifiers are tested with selected ECG time series and experimental results show that the MLP classifier offers a great potential in the supervised classification of ECG beats.en_US
dc.identifier.urihttps://dspace.univ-tlemcen.dz/handle/112/837en_US
dc.language.isoenen_US
dc.publisherUniversity of Tlemcenen_US
dc.subjectECG beat classifieren_US
dc.subjectsupervised classificationen_US
dc.subjectLVQ neural networksen_US
dc.titleSUPERVISED CLASSIFICATION OF ECG USING NEURAL NETWORKSen_US
dc.typeArticleen_US

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