A detailed characterization of complex networks using Information Theory.

ABSTRACT: Understanding the structure and the dynamics of networks is of paramount importance for many scientific fields that rely on network science. Complex network theory provides a variety of features that help in the evaluation of network behavior. However, such analysis can be confusing and misleading as there are many intrinsic properties for each network metric. Alternatively, Information Theory methods have gained the spotlight because of their ability to create a quantitative and robust characterization of such networks. In this work, we use two Information Theory quantifiers, namely Network Entropy and Network Fisher Information Measure, to analyzing those networks. Our approach detects non-trivial characteristics of complex networks such as the transition present in the Watts-Strogatz mo

SUBMITTER: Freitas CGS 

PROVIDER: S-EPMC6853913 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature