• DocumentCode
    2136120
  • Title

    Research on Noise Reduction Method for Chaotic Time Series and Its Application Based on Least Square Support Vector Machine

  • Author

    Xiang Xiaodong

  • Author_Institution
    Sch. of Manage., Fuzhou Univ., Fuzhou, China
  • fYear
    2009
  • fDate
    20-22 Sept. 2009
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    With regard to the need of non-noise data for the many existing chaos-discerning methods, the noise reduction method for chaotic time series based on least square support vector machine is proposed, followed by specific steps for its application. The result of emulation by Henon reflection system proves the effectiveness of this method.
  • Keywords
    chaos; least squares approximations; signal denoising; support vector machines; Henon reflection system; chaos-discerning methods; chaotic time series; least square support vector machine; noise reduction method; Acoustic reflection; Chaos; Cognition; Emulation; Least squares methods; Noise reduction; Nonlinear dynamical systems; Shadow mapping; Signal to noise ratio; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science, 2009. MASS '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4638-4
  • Electronic_ISBN
    978-1-4244-4639-1
  • Type

    conf

  • DOI
    10.1109/ICMSS.2009.5303374
  • Filename
    5303374