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Applicability of ordinal-array-based indicators to strange nonchaotic attractors
(Universität Kassel, 2017-06-12)
Time series are useful for modeling systems behavior, for predicting some events (catastrophes, epidemics, weather, . . . ) or for classification purposes (pattern recognition, pattern analysis). Among the existing data analysis algorithms, ordinal pattern based algorithms have been shown effective when dealing with simulation data. However, when applied to quasi-periodically forced systems, they fail to detect SNA and tori as regular dynamics. In this work we address this concern by defining ordinal array (OA) ...