Entropy characterization of random network models

Zufiria Zatarain, Pedro Jose and Barriales Valbuena, Iker (2017). Entropy characterization of random network models. "Entropy", v. 19 (n. 7); pp. 1-13. ISSN 1099-4300. https://doi.org/10.3390/e19070321.

Description

Title: Entropy characterization of random network models
Author/s:
  • Zufiria Zatarain, Pedro Jose
  • Barriales Valbuena, Iker
Item Type: Article
Título de Revista/Publicación: Entropy
Date: 2017
ISSN: 1099-4300
Volume: 19
Subjects:
Freetext Keywords: Complex networks; stochastic modelling; entropy; estimation
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Matemática Aplicada a las Tecnologías de la Información y las Comunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper elaborates on the Random Network Model (RNM) as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc.) and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainMTM2015-67396-PUnspecifiedUnspecifiedRedes complejas: modelado, dinámica y aplicaciones

More information

Item ID: 50810
DC Identifier: http://oa.upm.es/50810/
OAI Identifier: oai:oa.upm.es:50810
DOI: 10.3390/e19070321
Official URL: http://www.mdpi.com/1099-4300/19/7/321
Deposited by: Memoria Investigacion
Deposited on: 20 May 2018 10:10
Last Modified: 20 May 2018 10:10
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