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Detecting regular dynamics from time series using permutations slopes
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DOI：10.1016/j.cnsns.2015.03.008.png)
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Abstract
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In this paper we present the entropy related to the largest slope of the permutation as an efficient approach for distinguishing between regular and non-regular dynamics, as well as the similarities between this method and the three-state test (3ST) algorithm. We theoretically establish that for suitably chosen delay times, permutations generated in the case of regular dynamics present the same largest slope if their order is greater than the period of the underlying orbit. This investigation helps making a clear decision (even in a noisy environment) in the detection of regular dynamics with large periods for which PE gives an arbitrary nonzero complexity measure. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
Time series analysis
Ordinal patterns
Chaos detection
Entropy
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