Exploring Entropy-Based Classification of Time Series Using Visibility Graphs from Chaotic Maps
J. Alberto Conejero,
Andrei Velichko,
Òscar Garibo-i-Orts
et al.
Abstract:In this paper, we propose a method for assessing the effectiveness of entropy features using several chaotic mappings. We anlyze fuzzy entropy (FuzzyEn) and neural network entropy (NNetEn) on four discrete mappings: the logistic map, the sine map, the Planck map, and the two-memristor-based map, with a base length time series of 300 elements. FuzzyEn is shown to have improved global efficiency (GEFMCC) in the classification task compared to NNetEn. At the same time, there are local areas of the time series dyn… Show more
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