In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the
analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is …

Ordinal time series analysis is based on the idea to map time series to ordinal patterns, ie,
order relations between the values of a time series and not the values themselves, as …

The ordinal pattern-based complexity–entropy plane is a popular tool in nonlinear dynamics
for distinguishing stochastic signals (noise) from deterministic chaos. Its performance …

We use ordinal analysis and spatial permutation entropy to distinguish between eyes-open
and eyes-closed resting brain states. To do so, we analyze EEG data recorded with 64 …

We here propose a novel methodology, based on the concept of continuous ordinal
patterns, to preprocess time series and make explicit the non-linear temporal structures in …

This study presents the effectiveness of dynamic coupling as a synchronization strategy for
fractional chaotic systems. Using an auxiliary system as a link between the oscillators, we …

The dynamical approach represents a new branch in the understanding of functional brain
networks. Using simple indices to represent time connectivity and topological stability, we …

To evaluate the synchronization of bivariate time series has been a hot topic, and a number
of measures have been proposed. In this work, by introducing the ordinal pattern transition …

The original and amplitude permutations are two basic ordinal patterns; however, their
relationship has received little attention. This paper compares the original and amplitude …

In this article, we show that the recently introduced ordinal pattern dependence fits into the
axiomatic framework of general multivariate dependence measures, ie, measures of …