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

A 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...

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Vydáno v:Measurement : journal of the International Measurement Confederation Ročník 60; s. 121 - 128
Hlavní autoři: Miranda de Sá, Antonio Mauricio F.L., de Seixas, José Manoel, Costa Junior, José Dilermando, Ferreira, Danton Diego, Cerqueira, Augusto S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.01.2015
Témata:
Electrocardiography
Electromyography
Power quality
Principal Component Analysis
Single channel denoising
Electrocardiography
Single channel denoising
Electromyography
Power quality
Principal Component Analysis
ISSN:0263-2241, 1873-412X
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Shrnutí:A 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.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2014.09.079