Efficient ECG multi-level wavelet classification through neural network dimensionality reduction

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Campo DC	Valor	Idioma
dc.contributor.author	Andreão, Rodrigo Varejão	-
dc.contributor.author	Dorizzi, Bernadette	-
dc.contributor.author	Cortez, Paulo César	-
dc.contributor.author	Mota, João César Moura	-
dc.date.accessioned	2023-02-09T17:38:39Z	-
dc.date.available	2023-02-09T17:38:39Z	-
dc.date.issued	2002	-
dc.identifier.citation	MOTA, J. C. M. et al. Efficient ECG multi-level wavelet classification through neural network dimensionality reduction. In: WORKSHOP ON NEURAL NETWORKS FOR SIGNAL PROCESSING, 12., 2002, Martigny. Anais... Martigny: IEEE, 2002. p. 395-404.	pt_BR
dc.identifier.uri	http://www.repositorio.ufc.br/handle/riufc/70735	-
dc.description.abstract	In this article, we explore the use of a unique type of wavelets for ECG beat detection and classification. Once the different beats are segmented, classification is performed using at the input of a neural network different wavelet scales. This improves the noise resistance and allows a better representation of the different morphologies. The results, evaluated on the MIT/BIH database, are excellent (97.69% on the normal and PVC classes) thanks to the use of a regularization technique.	pt_BR
dc.language.iso	en	pt_BR
dc.publisher	Workshop on Neural Networks for Signal Processing	pt_BR
dc.title	Efficient ECG multi-level wavelet classification through neural network dimensionality reduction	pt_BR
dc.type	Artigo de Evento	pt_BR
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