Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in
time series (one-dimensional data). Some of these entropy metrics can be generalised to …

Using a graph-based approach, we propose a multiscale permutation entropy to explore the
complexity of multivariate time series over multiple time scales. This multivariate multiscale …

Nonlinear dynamics play an important role in the analysis of signals. A popular, readily
interpretable nonlinear measure is Permutation Entropy. It has recently been extended for …

In this paper, a new hybrid chaotic-quantum encryption model is investigated aiming to solve
the interception trouble of information transmission through insecure environment. In this …

We introduce Multivariate Multiscale Graph-based Dispersion Entropy (mvDEG), a novel,
computationally efficient method for analyzing multivariate time series data in graph and …

We propose a novel technique for exploring the complexity of multivariate time series
(possibly with different lengths) across multiple time scales using a new graph-based …

Changes in the variability of recorded physiological time-series have been connected with
transitions in the state of the monitored physiological system. The two primary paradigms …

Entropy metrics are nonlinear measures to quantify the complexity of time series. Among
them, permutation entropy is a common metric due to its robustness and fast computation …