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  • Research Article
  • Open Access

Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance

EURASIP Journal on Advances in Signal Processing20082008:526038

https://doi.org/10.1155/2008/526038

Received: 20 August 2007

Accepted: 10 April 2008

Published: 30 April 2008

Abstract

For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by using wavelet denoising method to avoid the mode mixture in the subsequent EMD procedure. Because traditional wavelet threshold denoising may exhibit pseudo-Gibbs phenomena in the neighborhood of discontinuities, we make use of translation invariance algorithm to suppress the artifacts. Then the processed signal is decomposed into intrinsic mode functions (IMFs) by EMD. The numerical results show that the proposed method is able to effectively avoid the mode mixture and retain the useful information.

Keywords

  • Information Technology
  • Quantum Information
  • Mode Function
  • Empirical Mode Decomposition
  • Translation Invariance

Publisher note

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Authors’ Affiliations

(1)
School of Electrical and Information Engineering, Dalian University of Technology, Dalian, China
(2)
Ship CAD Engineering Center, Dalian University of Technology, Dalian, China

Copyright

© Qin Pinle et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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