Maximum entropy principle in recurrence plot analysis on stochastic and chaotic systems

The recurrence analysis of dynamic systems has been studied since Poincaré’s seminal work. Since then, several approaches have been developed to study recurrence properties in nonlinear dynamical systems. In this work, we study the recently developed entropy of recurrence microstates. We propose a n...

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Bibliographic Details
Published in:Chaos (Woodbury, N.Y.) N.Y.), 2020-04, Vol.30 (4), p.043123-043123
Main Authors: Prado, T. L., Corso, G., dos Santos Lima, G. Z., Budzinski, R. C., Boaretto, B. R. R., Ferrari, F. A. S., Macau, E. E. N., Lopes, S. R.
Format: Article
Language:English
Subjects:
Chaos theory
Dynamical systems
Entropy
Liapunov exponents
Maximum entropy
Nonlinear systems
Parameters
Stochastic systems
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Summary:The recurrence analysis of dynamic systems has been studied since Poincaré’s seminal work. Since then, several approaches have been developed to study recurrence properties in nonlinear dynamical systems. In this work, we study the recently developed entropy of recurrence microstates. We propose a new quantifier, the maximum entropy ( S max). The new concept uses the diversity of microstates of the recurrence plot and is able to set automatically the optimum recurrence neighborhood ( ϵ—vicinity), turning the analysis free of the vicinity parameter. In addition, ϵ turns out to be a novel quantifier of dynamical properties itself. We apply S max and the optimum ϵ to deterministic and stochastic systems. The S max quantifier has a higher correlation with the Lyapunov exponent and, since it is a parameter-free measure, a more useful recurrence quantifier of time series.
ISSN:1054-1500
1089-7682
DOI:10.1063/1.5125921