A principal component-based algorithm for denoising in single channel data(PCA for denoising in single channel data)

dc.creatorSá, Antonio Mauricio Ferreira Leite Miranda de
dc.creatorSeixas, José Manoel de
dc.creatorCosta Junior, José Dilermando
dc.creatorFerreira, Danton Diego
dc.creatorCerqueira, Augusto Santiago
dc.date2017-09-22T17:14:21Z
dc.date2017-09-22T17:14:21Z
dc.date2015-01
dc.date.accessioned2023-09-28T20:04:06Z
dc.date.available2023-09-28T20:04:06Z
dc.identifierSÁ, A. M. F. L. M. de et al. A principal component-based algorithm for denoising in single channel data(PCA for denoising in single channel data). Measurement, Amsterdam, v. 60, p. 121-128, Jan. 2015.
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S0263224114004783
dc.identifierrepositorio.ufla.br/jspui/handle/1/15428
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9043650
dc.descriptionA denoising technique for single channel data is proposed. By assuming the observed signal to be the mixture of two unknown uncorrelated sources, an expression for the principal components (PC) of the set constituted by the signal and its k-sample delayed version is derived. The expression does not require matrix manipulations and may be hence useful when both speed and memory usage are crucial. The second PC was found to be a suitable estimate of one of the sources. Illustrations are provided for a simulated voltage signal corrupted by harmonics and transient disturbances as well as for a real electromyographic signal with electrocardiographic interference. A comparison with a standard, wavelet-based method for denoising is also provided.
dc.languageen_US
dc.publisherElsevier Science
dc.rightsrestrictAccess
dc.sourceMeasurement
dc.subjectPrincipal component analysis
dc.subjectSingle channel denoising
dc.subjectPower quality
dc.subjectElectromyography
dc.subjectElectrocardiography
dc.titleA principal component-based algorithm for denoising in single channel data(PCA for denoising in single channel data)
dc.typeArtigo


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