5 papers
Sample entropy for graph signals: An approach to nonlinear analysis of graph signals
Mei-San Maggie Lei, John Stewart Fabila Carrasco, Javier Escudero
We introduce a graph-signal generalisation of Sample Entropy, denoted SampEn, to quantify irregularity of graph signals on a continuous state space, complementing existing me…
Extreme Blazars Observed with MAGIC: Second Catalog Release
K. Abe, S. Abe, J. Abhir +353
Extremely high-peaked BL Lac objects - also named extreme blazars - are among the most energetic and persistent extragalactic accelerators in the Universe, defined by a synchrotron…
Sample entropy for graph signals: An approach to nonlinear dynamic analysis of data on networks
Mei-San Maggie Lei, John Stewart Fabila Carrasco, Javier Escudero
The recent extension of permutation entropy and its derivatives to graph signals has opened up new horizons for the analysis of complex, high-dimensional systems evolving on networ…
Graph Permutation Entropy: Extensions to the Continuous Case, A step towards Ordinal Deep Learning, and More
Om Roy, Avalon Campbell-Cousins, John Stewart Fabila Carrasco +2
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 t…
Graph-Based Multivariate Multiscale Dispersion Entropy: Efficient Implementation and Applications to Real-World Network Data
John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero
We introduce Multivariate Multiscale Graph-based Dispersion Entropy (mvDEG), a novel, computationally efficient method for analyzing multivariate time series data in graph and comp…