On quantification and maximization of information transfer in network dynamical systems.

ABSTRACT: Information flow among nodes in a complex network describes the overall cause-effect relationships among the nodes and provides a better understanding of the contributions of these nodes individually or collectively towards the underlying network dynamics. Variations in network topologies result in varying information flows among nodes. We integrate theories from information science with control network theory into a framework that enables us to quantify and control the information flows among the nodes in a complex network. The framework explicates the relationships between the network topology and the functional patterns, such as the information transfers in biological networks, information rerouting in sensor nodes, and influence patterns in social networks. We show that by designing or

SUBMITTER: Singh MS 

PROVIDER: S-EPMC10076297 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature