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Open AccessArticle

Amplitude- and Fluctuation-Based Dispersion Entropy

School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh EH9 3FB, UK
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Entropy 2018, 20(3), 210; https://doi.org/10.3390/e20030210
Received: 2 November 2017 / Revised: 5 February 2018 / Accepted: 13 March 2018 / Published: 20 March 2018
(This article belongs to the Special Issue Entropy in Signal Analysis)
Dispersion entropy (DispEn) is a recently introduced entropy metric to quantify the uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in the characterisation of time series. It includes a mapping step, but the effect of different mappings has not been studied yet. Here, we investigate the effect of linear and nonlinear mapping approaches in DispEn. We also inspect the sensitivity of different parameters of DispEn to noise. Moreover, we develop fluctuation-based DispEn (FDispEn) as a measure to deal with only the fluctuations of time series. Furthermore, the original and fluctuation-based forbidden dispersion patterns are introduced to discriminate deterministic from stochastic time series. Finally, we compare the performance of DispEn, FDispEn, permutation entropy, sample entropy, and Lempel–Ziv complexity on two physiological datasets. The results show that DispEn is the most consistent technique to distinguish various dynamics of the biomedical signals. Due to their advantages over existing entropy methods, DispEn and FDispEn are expected to be broadly used for the characterization of a wide variety of real-world time series. The MATLAB codes used in this paper are freely available at http://dx.doi.org/10.7488/ds/2326. View Full-Text
Keywords: nonlinear analysis; permutation entropy; dispersion entropy; fluctuation-based dispersion entropy; forbidden patterns nonlinear analysis; permutation entropy; dispersion entropy; fluctuation-based dispersion entropy; forbidden patterns
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Azami, H.; Escudero, J. Amplitude- and Fluctuation-Based Dispersion Entropy. Entropy 2018, 20, 210.

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