Authors:
- 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
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
About this book
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.
Authors and Affiliations
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Department of Computer Science and Systems Technology, University of Pannonia, Veszprém, Hungary
Dániel Leitold, Ágnes Vathy-Fogarassy
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MTA-PE Lendület Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary
János Abonyi
About the authors
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.
Bibliographic Information
Book Title: Network-Based Analysis of Dynamical Systems
Book Subtitle: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement
Authors: Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-030-36472-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-36471-7Published: 14 January 2020
eBook ISBN: 978-3-030-36472-4Published: 13 January 2020
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XIII, 110
Number of Illustrations: 10 b/w illustrations, 43 illustrations in colour
Topics: Computer Communication Networks, Control and Systems Theory, Vibration, Dynamical Systems, Control