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
Link To Document :
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