• DocumentCode
    1083133
  • Title

    Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding

  • Author

    Kopsinis, Yannis ; McLaughlin, Stephen

  • Author_Institution
    Sch. of Eng. & Electron., Univ. of Edinburgh, Edinburgh
  • Volume
    57
  • Issue
    4
  • fYear
    2009
  • fDate
    4/1/2009 12:00:00 AM
  • Firstpage
    1351
  • Lastpage
    1362
  • Abstract
    One of the tasks for which empirical mode decomposition (EMD) is potentially useful is nonparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can be appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance.
  • Keywords
    signal denoising; wavelet transforms; empirical mode decomposition; nonparametric signal denoising; wavelet thresholding principle; Empirical mode decomposition (EMD); signal denoising; wavelet thresholding;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2009.2013885
  • Filename
    4760240