Symbolic convergent cross mapping based on permutation mutual information

Xinlei Ge and Aijing Lin

Chaos, Solitons & Fractals, 2023, vol. 167, issue C

Abstract: In this paper, we extend convergent cross mapping (CCM) and propose symbolic CCM (SCCM), which uses mutual information based on permutation pattern instead of Pearson correlation coefficient to estimate cross-mapping ability. We numerically demonstrate that SCCM is a robust method for quantifying information flow between time series in chaotic systems, even under the influence of noises. Using the method, we analyze the multichannel EEG signals of ADHD children and control children, and identify the differences between the two groups of subjects with reliable results.

Keywords: Causality analysis; Convergent cross mapping; Permutation mutual information; Physiological system (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077922011717

DOI: 10.1016/j.chaos.2022.112992

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