| Autor: |
Prado TL; Departamento de Física, Universidade Federal do Paraná, Curitiba 81531-980, Brazil., Corso G; Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal 59078-970, Brazil., Dos Santos Lima GZ; Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal 59078-970, Brazil., Budzinski RC; Departamento de Física, Universidade Federal do Paraná, Curitiba 81531-980, Brazil., Boaretto BRR; Departamento de Física, Universidade Federal do Paraná, Curitiba 81531-980, Brazil., Ferrari FAS; Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba 39447-790, Brazil., Macau EEN; Laboratório Associado de Computação e Matemática Aplicada, Instituto Nacional de Pesquisas Espaciais, São José dos Campos 12227-010, Brazil., Lopes SR; Departamento de Física, Universidade Federal do Paraná, Curitiba 81531-980, Brazil. |
| Abstrakt: |
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. |
