Title :
Empirical Wavelet Transform
Author_Institution :
Dept. of Math. Los Angeles (UCLA), Univ. of California, Los Angeles, Los Angeles, CA, USA
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;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2013.2265222