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Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance

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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.

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Correspondence to Qin Pinle.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Pinle, Q., Yan, L. & Ming, C. Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance. EURASIP J. Adv. Signal Process. 2008, 526038 (2008) doi:10.1155/2008/526038

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Keywords

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