This book explores the key idea that the dynamical properties of complex
systems can be determined by effectively calculating specific structural
features using network science-based analysis. Furthermore, it argues
that certain dynamical behaviours can stem from the existence of
specific motifs in the network representation.
Over the last decade, network science has become a widely applied
methodology for the analysis of dynamical systems. Representing the
system as a mathematical graph allows several network-based methods to
be applied, and centrality and clustering measures to be calculated in
order to characterise and describe the behaviours of dynamical systems.
The applicability of the algorithms developed here is presented in the
form of well-known benchmark examples. The algorithms are supported by
more than 50 figures and more than 170 references; taken together, they
provide a good overview of the current state of network science-based
analysis of dynamical systems, and suggest further reading material for
researchers and students alike. The files for the proposed toolbox can
be downloaded from a corresponding website.