Entropy Characterization of Random Network Models
AbstractThis 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. View Full-Text
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Zufiria, P.J.; Barriales-Valbuena, I. Entropy Characterization of Random Network Models. Entropy 2017, 19, 321.
Zufiria PJ, Barriales-Valbuena I. Entropy Characterization of Random Network Models. Entropy. 2017; 19(7):321.Chicago/Turabian Style
Zufiria, Pedro J.; Barriales-Valbuena, Iker. 2017. "Entropy Characterization of Random Network Models." Entropy 19, no. 7: 321.
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