Efficient use of correlation entropy for analysing time series data

Pramana

R Misra²  G Ambika³  K P Harikrishnan1¹ 

[1] Department of Physics, The Cochin College, Cochin 682 002, India$$;Inter-University Centre for Astronomy and Astrophysics, Ganeshkhind, Pune 411 007, India$$;Indian Institute of Science Education and Research, Pune 411 021, India$$

关键词: Time series analysis;    correlation entropy;    coloured noise.;   

DOI  :  

学科分类：物理（综合）

来源: Indian Academy of Sciences

【 摘 要 】

The correlation dimension 𝐷2 and correlation entropy 𝐾2 are both important quantifiers in nonlinear time series analysis. However, use of 𝐷2 has been more common compared to 𝐾2 as a discriminating measure. One reason for this is that 𝐷2 is a static measure and can be easily evaluated from a time series. However, in many cases, especially those involving coloured noise, 𝐾2 is regarded as a more useful measure. Here we present an efficient algorithmic scheme to compute 𝐾2 directly from a time series data and show that 𝐾2 can be used as a more effective measure compared to 𝐷2 for analysing practical time series involving coloured noise.

【 授权许可】

Unknown