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dc.contributor.authorMejía González, Efraín A.-
dc.contributor.authorLópez-Leyva, Josué Aaron-
dc.contributor.authorEstrada Lechuga, Jessica-
dc.contributor.authorPonce Camacho, Miguel-
dc.contributor.otherCETYS Universidades_ES
dc.coverage.spatialThe 2nd International Conference on Energy, Electrical and Power Engineering 25–28 June 2019, Berkley, USAes_ES
dc.date.accessioned2020-09-15T18:48:15Z-
dc.date.available2020-09-15T18:48:15Z-
dc.date.issued2019-
dc.identifier.issn1742-6596-
dc.identifier.urihttps://repositorio.cetys.mx/handle/60000/879-
dc.descriptionScopuses_ES
dc.description.abstractIn this paper, an optimized algorithm based on temporal parameters analysis and correlation coefficients is presented in order to perform muscular diseases recognition. Statistical information was measured of three classes signals (Healthy, Myopathy and Neuropathy conditions). The temporal parameters that were initially proposed (14) were optimized based on the correlation coefficients. Thus, only 9 parameters were selected for optimized the algorithm, and the time required for training and recognition is ≈ 0.2s and ≈ 4ms, respectively.es_ES
dc.language.isoenes_ES
dc.rightsAtribución-NoComercial-CompartirIgual 2.5 México*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/2.5/mx/*
dc.subjectMuscular diseases recognitiones_ES
dc.subjectOptimized algorithmes_ES
dc.titleOptimized algorithm for muscular diseases recognition based on temporal parameters analysis and correlation coefficientses_ES
dc.typePresentationes_ES
dc.description.urlDOI: 10.1088/1742-6596/1304/1/012020es_ES
dc.subject.sedeCampus Ensenadaes_ES
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