• DocumentCode
    685011
  • Title

    Estimating properties of chaotic system based on S-NURBS resampling method

  • Author

    Chenxi Shao ; Qingqing Liu ; Tingting Wang ; Binghong Wang

  • Author_Institution
    Anhui Province Key Lab. of Software in Comput. & Commun., Univ. of Sci. & Technol. of China, Hefei, China
  • Volume
    01
  • fYear
    2013
  • fDate
    16-18 Aug. 2013
  • Firstpage
    413
  • Lastpage
    416
  • Abstract
    Physical properties of the chaotic system play important roles on studying the innate character and deciding the practical predictability of the dynamics. For a short piece of undersampled chaotic signals, it is very hard to abstract the physical properties of the signal source from the sequence. In this paper, we model this type of data with global S-NURBS method to reconstruct a smooth trajectory and resample the trajectory to get enough series. In this way, the problem of estimating the physical properties from small undersampled data is turned to the work of calculating the properties of the resampled time series. The new interpolation method is named as S-NURBS resampling method, and the simulation experiment demonstrates that the new method has a good performance in studying physical systems from the observed time series.
  • Keywords
    chaos; interpolation; signal sampling; splines (mathematics); time series; S-NURBS resampling method; chaotic system; global S-NURBS method; innate character; interpolation method; time series; trajectory resampling; undersampled chaotic signals; undersampled data; Chaos; Interpolation; Splines (mathematics); Surface reconstruction; Surface topography; Time series analysis; Trajectory; S-NURBS model; chaotic; estimating properties; resampling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measurement, Information and Control (ICMIC), 2013 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4799-1390-9
  • Type

    conf

  • DOI
    10.1109/MIC.2013.6757994
  • Filename
    6757994