The neural criticality hypothesis states that the brain may be poised in a critical state at a
boundary between different types of dynamics. Theoretical and experimental studies show …

This review provides a comparative overview of recent developments in the modelling of
cellular calcium oscillations. A large variety of mathematical models have been developed …

In 1980 and 1981, two pioneering papers laid the foundation for what became known as
nonlinear time-series analysis: the analysis of observed data—typically univariate—via …

Chaos: from simple models to complex systems aims to guide science and engineering
students through chaos and nonlinear dynamics from classical examples to the most recent …

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 …

In this paper we introduce a multiscale symbolic information-theory approach for
discriminating nonlinear deterministic and stochastic dynamics from time series associated …

It is unquestionable that time series forecasting is of paramount importance in many fields.
The most used machine learning models to address time series forecasting tasks are …

The only integrative approach to chaos and random fractal theory Chaos and random fractal
theory are two of the most important theories developed for data analysis. Until now, there …

This paper contributes to filling two gaps: i) the presence of a limited amount of studies
focused on tourism demand turning points, ii) the prevalent recourse to linear models in …

The study of nonlinear dynamical systems (NDS) dates back to the late nineteenth century,
although the majority of the progress has occurred in the last 30 years, and the majority of …