DocumentCode
81893
Title
Empirical Wavelet Transform
Author
Gilles, J.
Author_Institution
Dept. of Math. Los Angeles (UCLA), Univ. of California, Los Angeles, Los Angeles, CA, USA
Volume
61
Issue
16
fYear
2013
fDate
Aug.15, 2013
Firstpage
3999
Lastpage
4010
Abstract
Some recent methods, like the empirical mode decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful for many applications, the main issue with this approach is its lack of theory. This paper presents a new approach to build adaptive wavelets. The main idea is to extract the different modes of a signal by designing an appropriate wavelet filter bank. This construction leads us to a new wavelet transform, called the empirical wavelet transform. Many experiments are presented showing the usefulness of this method compared to the classic EMD.
Keywords
adaptive signal processing; channel bank filters; feature extraction; wavelet transforms; EMD; adaptive wavelets; empirical mode decomposition; empirical wavelet transform; signal mode extraction; wavelet filter bank; Adaptive filtering; empirical mode decomposition; wavelet;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2013.2265222
Filename
6522142
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