• DocumentCode
    711952
  • Title

    Nonlinear Dynamics Recognition in Solar Time Series Based on Recurrence Plot Techniques

  • Author

    Linhua Deng

  • Author_Institution
    Yunan Obs., Kunming, China
  • fYear
    2015
  • fDate
    24-26 April 2015
  • Firstpage
    843
  • Lastpage
    847
  • Abstract
    Recurrence is a fundamental property of many nonlinear dynamical systems, which can be exploited to characterize such dynamical system´s intrinsically behaviour in the phase space. The recurrence plot is a powerful and sensitive approach to quantify the nonlinear interaction of the two complex systems due to their coupling. As an example of typical data sets where the recurrence based methods have proven powerful, we apply two modern nonlinear approaches, including cross-recurrence plot and line of synchronization, to analyze the phase asynchrony between coronal index and sunspot numbers during the time interval from January 1939 to December 2008. It is found that, (1) the average value of their phase lags is about -10 months, implying that coronal index lags behind sunspot numbers during the considered time interval, (2) their phase relationship is not a simply linear relation, although they are highly correlated with each other. Our analysis results indicate that modern nonlinear approaches for the phase analysis between different time series are fairly useful and powerful.
  • Keywords
    solar power; sunlight; synchronisation; time series; coronal index; dynamical system intrinsically behaviour; nonlinear approaches; nonlinear dynamical systems; nonlinear dynamics recognition; nonlinear interaction; recurrence plot techniques; solar time series; synchronization; Control engineering; Information science; cross-recurrence plot; information processing; nonlinear dynamics recognition; time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-6849-0
  • Type

    conf

  • DOI
    10.1109/ICISCE.2015.192
  • Filename
    7120732