Reliable Multi-Fractal Characterization of Weighted Complex Networks: Algorithms and Implications.

ABSTRACT: Through an elegant geometrical interpretation, the multi-fractal analysis quantifies the spatial and temporal irregularities of the structural and dynamical formation of complex networks. Despite its effectiveness in unweighted networks, the multi-fractal geometry of weighted complex networks, the role of interaction intensity, the influence of the embedding metric spaces and the design of reliable estimation algorithms remain open challenges. To address these challenges, we present a set of reliable multi-fractal estimation algorithms for quantifying the structural complexity and heterogeneity of weighted complex networks. Our methodology uncovers that (i) the weights of complex networks and their underlying metric spaces play a key role in dictating the existence of multi-fractal scaling

SUBMITTER: Xue Y 

PROVIDER: S-EPMC5548933 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature