• DocumentCode
    2226857
  • Title

    The Study of The Denoising and the Trend Extraction Method of Signal

  • Author

    Anbing, Zhang ; Liu xinxia ; Liu Hui

  • Author_Institution
    Hebei Univ. of Eng., Handan, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    703
  • Lastpage
    706
  • Abstract
    Based on the capability of orthogonal wavelet transform in de-noise and trend extract function of EMD, a new noise filter and trend extraction model is built up. Then, simulated data is used to test the method. The following conclusions are drawn from these tests: (1) Orthogonal wavelet transform and EMD method can better mitigate the random errors which hide in periodic signal; (2) For signal with linear trend, Orthogonal wavelet transform filtering method is superior to EMD. (3) For signal with nonlinear trend, theoretic analysis and simulation results show that the new noise filter and trend extraction model is superior to EMD and to union simply wavelet and EMD method. This method greatly improves accuracy of the extracted deformation.
  • Keywords
    feature extraction; filtering theory; signal denoising; wavelet transforms; EMD method; deformation extraction; noise filter; orthogonal wavelet transform; random errors; signal denoising; trend extraction method; Data mining; Filtering; Filters; Noise generators; Noise level; Noise reduction; Signal processing; Testing; Wavelet coefficients; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.1296
  • Filename
    5455295