In the present work, we investigate phase correlations by recourse to the Shannon entropy. Using theoretical arguments, we show that the entropy provides an accurate measure of phase correlations in any dynamical system, in particular when dealing with a chaotic diffusion process. We apply this approach to different low-dimensional maps in order to show that indeed the entropy is very sensitive to the presence of correlations among the successive values of angular variables, even when it is weak. Later on, we apply this approach to unveil strong correlations in the time evolution of the phases involved in the Arnold’s Hamiltonian that lead to anomalous diffusion, particularly when the perturbation parameters are comparatively large. The obt...
The Markov and non-Markov processes in complex systems are examined with the help of dynamical infor...
We consider a general N-degrees-of-freedom nonlinear system which is chaotic and dissipative, and sh...
Entropy measures are widely applied to quantify the complexity of dynamical systems in diverse field...
In the present work, we investigate phase correlations by recourse to the Shannon entropy. Using the...
In the present work we extend and generalize the formulation of the Shannon entropy as a measure of ...
In the present work, we introduce two new estimators of chaotic diffusion based on the Shannon entro...
Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physica...
In the present effort, we revisit the Shannon entropy approach for the study of both the extent and ...
A method of estimating the Kolmogorov-Sinai (KS) entropy, herein referred to as the modified correla...
In this paper we present the concept of description of random processes in complex systems with disc...
The present work consists on a study of the dynamical stability of a 3-body system, taking advantage...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
A new expansion method to obtain time correlation functions and large deviation sta-tistical charact...
We consider the Markov and non-Markov processes in complex systems by the dynamical information Shan...
The Markov and non-Markov processes in complex systems are examined with the help of dynamical infor...
We consider a general N-degrees-of-freedom nonlinear system which is chaotic and dissipative, and sh...
Entropy measures are widely applied to quantify the complexity of dynamical systems in diverse field...
In the present work, we investigate phase correlations by recourse to the Shannon entropy. Using the...
In the present work we extend and generalize the formulation of the Shannon entropy as a measure of ...
In the present work, we introduce two new estimators of chaotic diffusion based on the Shannon entro...
Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physica...
In the present effort, we revisit the Shannon entropy approach for the study of both the extent and ...
A method of estimating the Kolmogorov-Sinai (KS) entropy, herein referred to as the modified correla...
In this paper we present the concept of description of random processes in complex systems with disc...
The present work consists on a study of the dynamical stability of a 3-body system, taking advantage...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
A new expansion method to obtain time correlation functions and large deviation sta-tistical charact...
We consider the Markov and non-Markov processes in complex systems by the dynamical information Shan...
The Markov and non-Markov processes in complex systems are examined with the help of dynamical infor...
We consider a general N-degrees-of-freedom nonlinear system which is chaotic and dissipative, and sh...
Entropy measures are widely applied to quantify the complexity of dynamical systems in diverse field...