• DocumentCode
    2618483
  • Title

    3A-EMD: A generalized approach for monovariate and multivariate EMD

  • Author

    Leureau, Julien F. ; Kachenoura, Amar ; Nunes, Jean-Claude ; Albera, Laurent ; Senhadji, Lotfi

  • Author_Institution
    UMR 642, Inserm, Rennes, France
  • fYear
    2010
  • fDate
    10-13 May 2010
  • Firstpage
    300
  • Lastpage
    303
  • Abstract
    EMD is an emerging topic in signal processing research and is applied in various practical fields. Its recent extension to multivariate signals, motivated by the need to jointly analyze multi-channel signals, is an active topic of research. However, all the existing etensions specifically hold either mono-, bi- or tri-variate signals or require multiple projections that complexity the original process. In this communication, a novel EMD approach called 3A-EMD is proposed. It is essentially based on the redefinition of the mean envelope operator and allows, under certain conditions, a straightforward decomposition of monovariate and multivariate signals without any change in the core of the algorithm. A comparative study with classical monovariate and bivariate methods is presented and shows the competitiveness of 3A-EMD. A trivariate decomposition is also given to illustrate the extension of the proposed algorithm to any signal dimension, D>2.
  • Keywords
    signal processing; 3A-EMD approach; empirical mode decomposition; monovariate EMD generalized approach; multichannel signal analysis; multivariate EMD generalized approach; multivariate signal decomposition; signal processing research; Artificial neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-7165-2
  • Type

    conf

  • DOI
    10.1109/ISSPA.2010.5605465
  • Filename
    5605465