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Empirical Mode Decomposition Based on Bistable Stochastic Resonance Denoising

  • Y.-J. Zhao
  • Y. Xu
  • H. Zhang
  • S.-B. Fan
  • Y.-G. Leng
Conference paper

Abstract

The empirical mode decomposition (EMD) of weak signals submerged in a heavy noise was conducted and a method of stochastic resonance (SR) used for noisy EMD was presented. This method used SR as pre-treatment of EMD to remove noise and detect weak signals. The experiment result proves that this method, compared with that using EMD directly, not only improve SNR, enhance weak signals, but also improve the decomposition performance and reduce the decomposition layers.

Keywords

Weak Signal Sine Wave Empirical Mode Decomposition Stochastic Resonance Local Average 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work is supported by national 863 project fund Grant # 2007AA04Z414 and National Natural Science Foundation of China Grant # 50675153.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Y.-J. Zhao
    • 1
  • Y. Xu
  • H. Zhang
  • S.-B. Fan
  • Y.-G. Leng
  1. 1.CSR Qingdao Sifang Locomotive and Rolling Stock CompanyQingdaoPeople’s Republic of China

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