• Efficient use of correlation entropy for analysing time series data

• # Fulltext

https://www.ias.ac.in/article/fulltext/pram/072/02/0325-0333

• # 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

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

• # Pramana – Journal of Physics

Volume 94, 2019
All articles
Continuous Article Publishing mode

• # Editorial Note on Continuous Article Publication

Posted on July 25, 2019