Permutation entropy for graph signals
JS Fabila-Carrasco, C Tan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …
time series (one-dimensional data). Some of these entropy metrics can be generalised to …
Spectral preorder and perturbations of discrete weighted graphs
In this article, we introduce a geometric and a spectral preorder relation on the class of
weighted graphs with a magnetic potential. The first preorder is expressed through the …
weighted graphs with a magnetic potential. The first preorder is expressed through the …
A noise-robust Multivariate Multiscale Permutation Entropy for two-phase flow characterisation
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 …
complexity of multivariate time series over multiple time scales. This multivariate multiscale …
Graph-based Multivariate Multiscale Permutation Entropy: Study of Robustness to Noise and Application to Two-Phase Flow Data
JS Fabila-Carrasco, C Tan… - 2023 31st European …, 2023 - ieeexplore.ieee.org
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 …
(possibly with different lengths) across multiple time scales using a new graph-based …
Dispersion entropy: A Measure of Irregularity for Graph Signals
JS Fabila-Carrasco, C Tan, J Escudero - arXiv preprint arXiv:2303.18079, 2023 - arxiv.org
We introduce a novel method, called Dispersion Entropy for Graph Signals, $ DE_G $, as a
powerful tool for analysing the irregularity of signals defined on graphs. We demonstrate the …
powerful tool for analysing the irregularity of signals defined on graphs. We demonstrate the …