SUPERVISED CLASSIFICATION OF ECG USING NEURAL NETWORKS

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Élément Dublin Core	Valeur	Langue
dc.contributor.author	Belgacem, N	-
dc.contributor.author	Chikh, MA	-
dc.contributor.author	Bereksi Reguig, F	-
dc.date.accessioned	2012-05-23T14:52:54Z	-
dc.date.available	2012-05-23T14:52:54Z	-
dc.date.issued	2003-09-27	-
dc.identifier.uri	http://dspace.univ-tlemcen.dz/handle/112/837	-
dc.description	Conférence Internationale sur les Systèmes de Télécommunication , d’Electronique Médicale et d’Automatique, CISTEMA’2003	-
dc.description.abstract	In 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.language.iso	en	en_US
dc.publisher	University of Tlemcen	en_US
dc.subject	ECG beat classifier	en_US
dc.subject	supervised classification	en_US
dc.subject	LVQ neural networks	en_US
dc.title	SUPERVISED CLASSIFICATION OF ECG USING NEURAL NETWORKS	en_US
dc.type	Article	en_US
Collection(s) :	Articles internationaux

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