DocumentCode
1083133
Title
Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding
Author
Kopsinis, Yannis ; McLaughlin, Stephen
Author_Institution
Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh
Volume
57
Issue
4
fYear
2009
fDate
4/1/2009 12:00:00 AM
Firstpage
1351
Lastpage
1362
Abstract
One of the tasks for which empirical mode decomposition (EMD) is potentially useful is nonparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can be appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance.
Keywords
signal denoising; wavelet transforms; empirical mode decomposition; nonparametric signal denoising; wavelet thresholding principle; Empirical mode decomposition (EMD); signal denoising; wavelet thresholding;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2009.2013885
Filename
4760240
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