Network Dynamics as an Inverse Problem
Reconstruction, Design and Optimality
von Jose Luis Casadiego Bastidas
Datum der mündl. Prüfung:2016-01-13
Erschienen:2016-12-16
Betreuer:Prof. Dr. Marc Timme
Gutachter:Prof. Dr. Reiner Kree
Gutachter:Prof. Dr. Ulrich Parlitz
Gutachter:Prof. Dr. Stephan Herminghaus
Gutachter:Prof. Dr. Theo Geisel
Gutachter:Prof. Dr. Patrick Cramer
Dateien
Name:ND_as_Inverse_Problem.pdf
Size:16.1Mb
Format:PDF
Description:Doctoral thesis
Zusammenfassung
Englisch
In this thesis, we take a general view on the study of networks from inverse perspectives. By proposing a general representation for the dynamics of networks in terms of explicit dependencies among units, we develop new concepts for understanding, among other things, (i) how disparate networks achieve identical dynamics, and (ii) how we may reconstruct the structural connectivity of networks regardless of the type of network under study (e.g. gene regulatory networks, metabolic networks or neural networks). Specifically, here we heavily rely on concepts and tools coming from nonlinear dynamics and linear algebra to introduce physics-inspired inverse approaches for explaining the fundamental mechanisms for revealing connections in networks. Furthermore, the content and results of this thesis are self-sufficient, such that the reader may not need to refer to additional scientific sources.
Keywords: network + inference + reconstruction + inverse + dynamics + inferring + revealing + reconstructing + dynamical + systems + correlations + transfer + entropy + synaptic + connectivity + neural + connections + links + reveal + discover + ARNI + event + space; explict + dependencies