Network-Based Analysis of Dynamical Systems

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.

Describes the structural analysis of the network-based representation of dynamical systems Addresses the improvement of input and output configurations of dynamical systems, presenting five methods for decreasing their relative degree on the basis of the motifs revealed in the networks Discusses the analysis of the correlation between the structural properties of network-based representations and dynamical behaviours of dynamical systems

Autorentext

Dr. János Abonyi is a Full Professor of Computer Science and Chemical Engineering at the Department of Process Engineering, University of Pannonia, Veszprém, Hungary. His other publications include the Springer titles Interpretability of Computational Intelligence-Based Regression Models, and (with Dr. Vathy-Fogarassy) Graph-Based Clustering and Data Visualization Algorithms.

Dr. Ágnes Vathy-Fogarassy is an Associate Professor at the Department of Computer Science and Systems Technology at the University of Pannonia.

Dániel Leitold is an Assistant Lecturer at the University of Pannonia.

Zusammenfassung

"I would like to recommend this book to students and researchers interested in network science-based controllability and observability analysis of complex systems." (Jin Liang, zbMATH 1543.93002, 2024)

Inhalt

1. Introduction.- 2. Structural Controllability and Observability Analysis in Complex Networks.- 3. Reduction of Relative Degree by Optimal Control and Sensor Placement.- 4. Applications to the analysis of Heat Exchanger Networks.- 5. The NOCAD MATLAB/Octave Toolbox Developed for the Analysis of Dynamical Systems.- 6. Summary.