Entropies of complex networks with hierarchically constrained topologies
Disordered Systems and Neural Networks
2009-11-13 v2 Statistical Mechanics
Abstract
The entropy of a hierarchical network topology in an ensemble of sparse random networks with "hidden variables" associated to its nodes, is the log-likelihood that a given network topology is present in the chosen ensemble.We obtain a general formula for this entropy,which has a clear simple interpretation in some simple limiting cases. The results provide new keys with which to solve the general problem of "fitting" a given network with an appropriate ensemble of random networks.
Cite
@article{arxiv.0803.1247,
title = {Entropies of complex networks with hierarchically constrained topologies},
author = {Ginestra Bianconi and Anthony C. C. Coolen and Conrad J. Perez Vicente},
journal= {arXiv preprint arXiv:0803.1247},
year = {2009}
}
Comments
(18 pages)