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

被引：10
|
作者：
Miranda de Sa, Antonio Mauricio F. L. [1 ]
de Seixas, Jose Manoel [2 ]
Costa Junior, Jose Dilermando [1 ]
Ferreira, Danton Diego [3 ]
Cerqueira, Augusto S. [4 ]
机构：
[1] Univ Fed Rio de Janeiro, Biomed Engn Program, COPPE, BR-21941972 Rio De Janeiro, RJ, Brazil
[2] Univ Fed Rio de Janeiro, Signal Proc Lab, COPPE POLI, BR-21941972 Rio De Janeiro, RJ, Brazil
[3] Univ Fed Rio de Janeiro, Signal Proc Lab, COPPE POLI, BR-21941972 Rio De Janeiro, RJ, Brazil
[4] Univ Fed Juiz de Fora, Elect Engn Program, Juiz De Fora, MG, Brazil
来源：
MEASUREMENT | 2015年 / 60卷
关键词：
Principal Component Analysis; Single channel denoising; Power quality; Electromyography; Electrocardiography;
D O I：
10.1016/j.measurement.2014.09.079
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码：121 / 128
页数：8
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