• 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