In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Entropy is a powerful tool for the analysis of time series, as it allows describing the
probability distributions of the possible state of a system, and therefore the information …

This review addresses a central question in the field of complex systems: given a fluctuating
(in time or space), sequentially measured set of experimental data, how should one analyze …

The application of methods drawn from nonlinear and stochastic dynamics to the analysis of
cardiovascular time series is reviewed, with particular reference to the identification of …

Nonlinear time series analysis is an active field of research that studies the structure of
complex signals in order to derive information of the process that generated those series, for …

The dynamical systems found in nature are rarely isolated. Instead they interact and
influence each other. The coupling functions that connect them contain detailed information …

Since the operative definition given by CWJ Granger of an idea expressed by N. Wiener, the
Wiener-Granger causality (WGC) has been one of the most relevant concepts exploited by …

In this paper an approach to identify delay phenomena from time series is developed. We
show that it is possible to perform a reliable time delay identification by using quantifiers …

Epilepsy is a malfunction of the brain that affects over 50 million people worldwide. Epileptic
seizures are usually characterized by an abnormal synchronized firing of neurons involved …

Recently, methods have been developed to analyse couplings in dynamic systems. In the
field of medical analysis of complex cardiovascular and cardiorespiratory systems, there is …