• Efficient use of correlation entropy for analysing time series data

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    • Keywords


      Time series analysis; correlation entropy; coloured noise.

    • Abstract


      The correlation dimension $D_{2}$ and correlation entropy $K_{2}$ are both important quantifiers in nonlinear time series analysis. However, use of $D_{2}$ has been more common compared to $K_{2}$ as a discriminating measure. One reason for this is that $D_{2}$ is a static measure and can be easily evaluated from a time series. However, in many cases, especially those involving coloured noise, $K_{2}$ is regarded as a more useful measure. Here we present an efficient algorithmic scheme to compute $K_{2}$ directly from a time series data and show that $K_{2}$ can be used as a more effective measure compared to $D_{2}$ for analysing practical time series involving coloured noise.

    • Author Affiliations


      K P Harikrishnan1 R Misra2 G Ambika3

      1. Department of Physics, The Cochin College, Cochin 682 002, India
      2. Inter-University Centre for Astronomy and Astrophysics, Ganeshkhind, Pune 411 007, India
      3. Indian Institute of Science Education and Research, Pune 411 021, India
    • Dates

  • Pramana – Journal of Physics | News

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      Posted on July 25, 2019

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