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
Link To Document :
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