Download or read book Network Based Analysis of Dynamical Systems written by Dániel Leitold and published by Springer Nature. This book was released on 2020-01-13 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Dynamical Systems on Networks written by Mason Porter and published by Springer. This book was released on 2016-03-31 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Applied Mathematics, and co-Director of MACSI, at the University of Limerick, Ireland.

Download or read book Synchronization in Complex Networks of Nonlinear Dynamical Systems written by Chai Wah Wu and published by World Scientific. This book was released on 2007 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ideas from systems theory, linear algebra and graph theory and the synergy between them that are necessary to derive synchronization conditions. Many of the results, which have been obtained fairly recently and have until now not appeared in textbook form, are presented with complete proofs. This text is suitable for graduate-level study or for researchers who would like to be better acquainted with the latest research in this area. Sample Chapter(s). Chapter 1: Introduction (76 KB). Contents: Graphs, Networks, Laplacian Matrices and Algebraic Connectivity; Graph Models; Synchronization in Networks of Nonlinear Continuous-Time Dynamical Systems; Synchronization in Networks of Coupled Discrete-Time Systems; Synchronization in Network of Systems with Linear Dynamics; Agreement and Consensus Problems in Groups of Interacting Agents. Readership: Graduate students and researchers in physics, applied mathematics and engineering.

Download or read book Modelling Analysis and Control of Networked Dynamical Systems written by Ziyang Meng and published by Springer Nature. This book was released on 2021-10-15 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a comprehensive exploration of new tools for modelling, analysis, and control of networked dynamical systems. Expanding on the authors’ previous work, this volume highlights how local exchange of information and cooperation among neighboring agents can lead to emergent global behaviors in a given networked dynamical system. Divided into four sections, the first part of the book begins with some preliminaries and the general networked dynamical model that is used throughout the rest of the book. The second part focuses on synchronization of networked dynamical systems, synchronization with non-expansive dynamics, periodic solutions of networked dynamical systems, and modulus consensus of cooperative-antagonistic networks. In the third section, the authors solve control problems with input constraint, large delays, and heterogeneous dynamics. The final section of the book is devoted to applications, studying control problems of spacecraft formation flying, multi-robot rendezvous, and energy resource coordination of power networks. Modelling, Analysis, and Control of Networked Dynamical Systems will appeal to researchers and graduate students interested in control theory and its applications, particularly those working in networked control systems, multi-agent systems, and cyber-physical systems. This volume can also be used in advanced undergraduate and graduate courses on networked control systems and multi-agent systems.

Download or read book Identification of Continuous time Dynamical Systems written by and published by . This book was released on 1993 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-delay mappings constructed using neural networks have proven successful performing nonlinear system identification; however, because of their discrete nature, their use in bifurcation analysis of continuous-tune systems is limited. This shortcoming can be avoided by embedding the neural networks in a training algorithm that mimics a numerical integrator. Both explicit and implicit integrators can be used. The former case is based on repeated evaluations of the network in a feedforward implementation; the latter relies on a recurrent network implementation. Here the algorithms and their implementation on parallel machines (SIMD and MIMD architectures) are discussed.

Download or read book Discrete Networked Dynamic Systems written by Magdi S. Mahmoud and published by Academic Press. This book was released on 2020-11-06 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs. This book addresses advanced analytical tools for characterization control, estimation and design of networked dynamic systems over fixed, probabilistic and time-varying graphs Provides coherent results on adopting a set-theoretic framework for critically examining problems of the analysis, performance and design of discrete distributed systems over graphs Deals with both homogeneous and heterogeneous systems to guarantee the generality of design results

Download or read book Recurrence Quantification Analysis written by Charles L. Webber, Jr. and published by Springer. This book was released on 2014-07-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of recurrences in dynamical systems by using recurrence plots and their quantification is still an emerging field. Over the past decades recurrence plots have proven to be valuable data visualization and analysis tools in the theoretical study of complex, time-varying dynamical systems as well as in various applications in biology, neuroscience, kinesiology, psychology, physiology, engineering, physics, geosciences, linguistics, finance, economics, and other disciplines. This multi-authored book intends to comprehensively introduce and showcase recent advances as well as established best practices concerning both theoretical and practical aspects of recurrence plot based analysis. Edited and authored by leading researcher in the field, the various chapters address an interdisciplinary readership, ranging from theoretical physicists to application-oriented scientists in all data-providing disciplines.

Download or read book Analysis of Dynamical and Cognitive Systems written by Stig I. Andersson and published by Springer Science & Business Media. This book was released on 1995-01-26 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the documentation of the advanced course on Analysis of Dynamical and Cognitive Systems, held during the Summer University of Southern Stockholm in Stockholm, Sweden in August 1993. The volume contains eight carefully revised full versions of the invited three-to-four hour presentations as well as two abstracts. As a consequence of the interdisciplinary topic, several aspects of dynamical and cognitive systems are addressed: there are three papers on computability and undecidability, five tutorials on diverse aspects of universal cellular neural networks, and two presentations on dynamical systems and complexity.

Download or read book Nonlinear Dynamical Systems written by Irwin W. Sandberg and published by John Wiley & Sons. This book was released on 2001-02-21 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sechs erfahrene Autoren beschreiben in diesem Band ein Spezialgebiet der neuronalen Netze mit Anwendungen in der Signalsteuerung, Signalverarbeitung und Zeitreihenanalyse. Ein zeitgemäßer Beitrag zur Behandlung nichtlinear-dynamischer Systeme!

Download or read book Stability Analysis of Neural Networks written by Grienggrai Rajchakit and published by Springer Nature. This book was released on 2021-12-05 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses recent research on the stability of various neural networks with constrained signals. It investigates stability problems for delayed dynamical systems where the main purpose of the research is to reduce the conservativeness of the stability criteria. The book mainly focuses on the qualitative stability analysis of continuous-time as well as discrete-time neural networks with delays by presenting the theoretical development and real-life applications in these research areas. The discussed stability concept is in the sense of Lyapunov, and, naturally, the proof method is based on the Lyapunov stability theory. The present book will serve as a guide to enable the reader in pursuing the study of further topics in greater depth and is a valuable reference for young researcher and scientists.

Download or read book Propagation Dynamics on Complex Networks written by Xinchu Fu and published by John Wiley & Sons. This book was released on 2013-12-17 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores the emerging subject of epidemic dynamics on complex networks, including theories, methods, and real-world applications Throughout history epidemic diseases have presented a serious threat to human life, and in recent years the spread of infectious diseases such as dengue, malaria, HIV, and SARS has captured global attention; and in the modern technological age, the proliferation of virus attacks on the Internet highlights the emergent need for knowledge about modeling, analysis, and control in epidemic dynamics on complex networks. For advancement of techniques, it has become clear that more fundamental knowledge will be needed in mathematical and numerical context about how epidemic dynamical networks can be modelled, analyzed, and controlled. This book explores recent progress in these topics and looks at issues relating to various epidemic systems. Propagation Dynamics on Complex Networks covers most key topics in the field, and will provide a valuable resource for graduate students and researchers interested in network science and dynamical systems, and related interdisciplinary fields. Key Features: Includes a brief history of mathematical epidemiology and epidemic modeling on complex networks. Explores how information, opinion, and rumor spread via the Internet and social networks. Presents plausible models for propagation of SARS and avian influenza outbreaks, providing a reality check for otherwise abstract mathematical modeling. Considers various infectivity functions, including constant, piecewise-linear, saturated, and nonlinear cases. Examines information transmission on complex networks, and investigates the difference between information and epidemic spreading.

Download or read book Data Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Download or read book Node influence in Network based Discrete Dynamical Systems written by Thomas Parmer and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many complex systems can be modeled as network-based discrete dynamical systems, where individual nodes (representing some variable of interest) are connected by edges that describe their interactions. Each node can take on different states relevant to the network under investigation (for example, a gene may be turned ON or OFF in a genetic regulatory network, or a person may be Infected or Susceptible to a disease in an epidemiological network). These networks are frequently studied by analyzing global properties such as fixed points, robustness (sensitivity to perturbation), and functional organization (modularity). A fundamental problem in complex systems science is to understand how interactions between individual components of a system give rise to such properties; in other words, how can the influence of a node, or set of nodes, be measured and how does it affect the large-scale dynamics of the system? Understanding this influence is crucial to characterize, predict, and control complex systems.Traditional lines of inquiry often analyze only the network structure or assume that the entire network configuration is known (i.e., the state value of all nodes in the network). In practice, however, a network's structure may not be a good predictor of its dynamics and furthermore, it is reasonable to assume that some nodes may not be measurable or controllable. Some recent approaches, such as causal inference methods, do not make such assumptions; still, calculating influence is in general a NP-hard problem and thus there is a need to further develop feasible approximate methods that work well in practice. This dissertation focuses on methods to calculate node influence and uncover dynamical properties of a network (modular organization, attractor control sets, size of perturbation cascades) that depend only on limited (partial) knowledge of the network configuration. I begin by reviewing the literature on node influence and related problems (influence maximization, control, and modularity), with special focus on methods that utilize either causal inference or approximations of dynamics. I then expand upon these methods with my own contributions to the field. First, I utilize the the existing concept of pathway modules on a dynamical map to define complex (synergistic) modules and use these to describe a network's dynamics by its underlying causal mechanisms (by calculating direct node influence) and measure its dynamical modularity. Next I use a mean-field approximation of a node's state based on iterative update of the states of its inputs (the IBMFA) to estimate the influence of that node on long-term configurations and attractors of a network, finding that the approximation performs well in comparison to actual simulations of the system. Finally, I define a thresholded representation of the dynamics (a generalized threshold network) to study different structural representations of the node update functions. I use these different representations and the IBMFA to calculate node influence and find that the choice of which method to use depends on the connectivity of the graph and the precision required. These methods are applied to various networks including random Boolean networks and biological signaling and regulatory networks, with examples given of additional use cases (such as linear threshold models and game-theoretic networks). Taken together, they help to elucidate the role of individual components within complex systems, with applications to dynamical modularity, influence maximization, and attractor/target control. Throughout I try to bridge the gap between literature on dynamical networks (e.g., logical models, Boolean networks) and dynamical processes on networks (e.g., epidemic and information spreading).

Download or read book Recent Advances in Control Problems of Dynamical Systems and Networks written by Ju H. Park and published by Springer Nature. This book was released on 2020-08-11 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book introduces readers to new analytical techniques and controller design schemes used to solve the emerging “hottest” problems in dynamic control systems and networks. In recent years, the study of dynamic systems and networks has faced major changes and challenges with the rapid advancement of IT technology, accompanied by the 4th Industrial Revolution. Many new factors that now have to be considered, and which haven’t been addressed from control engineering perspectives to date, are naturally emerging as the systems become more complex and networked. The general scope of this book includes the modeling of the system itself and uncertainty elements, examining stability under various criteria, and controller design techniques to achieve specific control objectives in various dynamic systems and networks. In terms of traditional stability matters, this includes the following special issues: finite-time stability and stabilization, consensus/synchronization, fault-tolerant control, event-triggered control, and sampled-data control for classical linear/nonlinear systems, interconnected systems, fractional-order systems, switched systems, neural networks, and complex networks. In terms of introducing graduate students and professional researchers studying control engineering and applied mathematics to the latest research trends in the areas mentioned above, this book offers an excellent guide.

Download or read book Analysis and Control of Complex Dynamical Systems written by Kazuyuki Aihara and published by Springer. This book was released on 2015-03-20 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

Download or read book Network Information Systems written by Wassim M. Haddad and published by SIAM. This book was released on 2023-06-06 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a unique treatment of network control systems. Drawing from fundamental principles of dynamical systems theory and dynamical thermodynamics, the authors develop a continuous-time, discrete-time, and hybrid dynamical system and control framework for linear and nonlinear large-scale network systems. The proposed framework extends the concepts of energy, entropy, and temperature to undirected and directed information networks. Continuous-time, discrete-time, and hybrid thermodynamic principles are used to design distributed control protocol algorithms for static and dynamic networked systems in the face of system uncertainty, exogenous disturbances, imperfect system network communication, and time delays. Network Information Systems: A Dynamical Systems Approach is written for applied mathematicians, dynamical systems theorists, control theorists, and engineers. Researchers and graduate students in a variety of fields who seek a fundamental understanding of the rich behavior of controlled large-scale network systems will also find this book useful. This book can be used for a first course on control design of large-scale network systems, such as control protocols for network systems, network information systems, a dynamical systems approach to network systems, and network thermodynamic systems. The prerequisites are a first course in nonlinear systems theory and a first course in advanced (multivariable) calculus.

Download or read book Dynamical Systems with Applications using Mathematica written by Stephen Lynch and published by Springer Science & Business Media. This book was released on 2007-10-01 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the theory of dynamical systems with the aid of the Mathematica® computer algebra package. The book has a very hands-on approach and takes the reader from basic theory to recently published research material. Emphasized throughout are numerous applications to biology, chemical kinetics, economics, electronics, epidemiology, nonlinear optics, mechanics, population dynamics, and neural networks. Theorems and proofs are kept to a minimum. The first section deals with continuous systems using ordinary differential equations, while the second part is devoted to the study of discrete dynamical systems.