Quantification of Graph Complexity Based on the Edge Weight Distribution Balance: Application to Brain Networks.

Abstract

The aim of this study was to introduce a novel global measure of graph complexity: Shannon graph complexity (SGC). This measure was specifically developed for weighted graphs, but it can also be applied to binary graphs. The proposed complexity measure was designed to capture the interplay between two properties of a system: the 'information' (calculated by… (More)
DOI: 10.1142/S0129065717500320

Cite this paper

@article{GomezPilar2018QuantificationOG, title={Quantification of Graph Complexity Based on the Edge Weight Distribution Balance: Application to Brain Networks.}, author={Javier Gomez-Pilar and Jes{\'u}s Poza and Alejandro Bachiller and Carlos G{\'o}mez and Pablo N{\'u}{\~n}ez and Alba Lubeiro and Vicente Molina and Roberto Hornero}, journal={International journal of neural systems}, year={2018}, volume={28 1}, pages={1750032} }