4.7 Article

Empirical Wavelet Transform

Journal

IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 61, Issue 16, Pages 3999-4010

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2013.2265222

Keywords

Adaptive filtering; empirical mode decomposition; wavelet

Funding

  1. NSF [DMS-0914856, DMS-1118971]
  2. ONR [N00014-08-1-1119, N0014-09-1-0360]
  3. ONR MURI USC
  4. UC Lab Fees Research
  5. Keck Foundation

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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.

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