Abstract
A powerful approach is proposed for the characterization of chaotic signals. It is based on the combined use of two classes of indicators: (i) the probability of suitable symbolic sequences (obtained from the ordinal patterns of the corresponding time series); (ii) the width of the corresponding cylinder sets. This way, much information can be extracted and used to quantify the complexity of a given signal. As an example of the potentiality of the method, I introduce a modified permutation entropy which allows for quantitative estimates of the Kolmogorov-Sinai entropy in hyperchaotic models, where other methods would be unpractical. As a by-product, estimates of the fractal dimension of the underlying attractors are possible as well.
Original language | English |
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Article number | 144101 |
Journal | Physical Review Letters |
Volume | 118 |
Issue number | 4 |
DOIs | |
Publication status | Published - 7 Apr 2017 |
Bibliographical note
AcknowledgementsThe author wishes to acknowledge G. Giacomelli, M. Mulansky, and L. Ricci for early discussions.