®®®® SIIA Público

Título del libro: Mathematical Foundations And Applications Of Graph Entropy
Título del capítulo: Entropy and Renormalization in Chaotic Visibility Graphs

Autores UNAM:
ALBERTO ROBLEDO NIETO;
Autores externos:

Idioma:
Inglés
Año de publicación:
2016
Palabras clave:

Chaotic visibility graphs; Graph entropy; Graph kolmogorov-sinai entropy; Nonlinear time series analysis; Renormalization; Shannon entropy


Resumen:

This chapter defines a graph entropy and process of renormalization for visibility graphs that characterize these routes and analyze the relationship between the flow of renormalization and the extremes of the entropy function. Nonlinear time series analysis develops from techniques such as nonlinear correlation functions, embedding algorithms, multrifractal spectra, and projection theorem tools that increase in complexity parallel to the complexity of the process/series under study. The chapter discusses the several definitions of entropy applied to visibility graphs: graph entropy, and graph Kolmogorov-Sinai entropy. These entropies defined in the graph are equivalent to Shannon entropy and Kolmogorov-Sinai entropy of the time series. One have seen that critical points correspond to extremals in the process of graph entropy maximization, which produces degree distribution of the visibility graphs at the critical points and at two trivial points: the random series and constant series. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA. All rights reserved.


Entidades citadas de la UNAM: