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Permutation Entropy: New Ideas and Challenges

Institute of Mathematics, University of Lübeck, Lübeck D-23562, Germany
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Academic Editor: Osvaldo Anibal Rosso
Entropy 2017, 19(3), 134; https://doi.org/10.3390/e19030134
Received: 17 February 2017 / Revised: 17 March 2017 / Accepted: 17 March 2017 / Published: 21 March 2017
(This article belongs to the Special Issue Entropy and Electroencephalography II)
Over recent years, some new variants of Permutation entropy have been introduced and applied to EEG analysis, including a conditional variant and variants using some additional metric information or being based on entropies that are different from the Shannon entropy. In some situations, it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data. View Full-Text
Keywords: ordinal patterns; Permutation entropy; Approximate entropy; Sample entropy; Conditional entropy of ordinal patterns; Kolmogorov–Sinai entropy; classification ordinal patterns; Permutation entropy; Approximate entropy; Sample entropy; Conditional entropy of ordinal patterns; Kolmogorov–Sinai entropy; classification
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Keller, K.; Mangold, T.; Stolz, I.; Werner, J. Permutation Entropy: New Ideas and Challenges. Entropy 2017, 19, 134.

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