Enhanced Empirical Mode Decomposition using a Novel Sifting-Based Interpolation Points Detection

  • Authors:

  • Yannis Kopsinis;Stephen McLaughlin

  • Affiliations:

  • IDCOM,School of Engineering and Electronics, The University of Edinburgh, King's Buildings, EH9 3JL, Edinburgh;IDCOM,School of Engineering and Electronics, The University of Edinburgh, King's Buildings, EH9 3JL, Edinburgh

  • Venue:
  • SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
  • Year:
  • 2007

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Abstract

Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage ntage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.