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 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 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 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 Logical Modeling of Cellular Processes From Software Development to Network Dynamics written by Matteo Barberis and published by Frontiers Media SA. This book was released on 2019-08-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical models have become invaluable tools for understanding the intricate dynamic behavior of complex biochemical and biological systems. Among computational strategies, logical modeling has been recently gaining interest as an alternative approach to address network dynamics. Due to its advantages, including scalability and independence of kinetic parameters, the logical modeling framework is becoming increasingly popular to study the dynamics of highly interconnected systems, such as cell cycle progression, T cell differentiation and gene regulation. Novel tools and standards have been developed to increase the interoperability of logical models, which can now be employ to respond a variety of biological questions. This Research Topic brings together the most recent and cutting-edge approaches in the area of logical modeling including, among others, novel biological applications, software development and model analysis techniques.

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 Discrete and Continuous Models in the Theory of Networks written by Fatihcan M. Atay and published by Springer Nature. This book was released on 2020-09-03 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains contributions from the participants of the research group hosted by the ZiF - Center for Interdisciplinary Research at the University of Bielefeld during the period 2013-2017 as well as from the conclusive conference organized at Bielefeld in December 2017. The contributions consist of original research papers: they mirror the scientific developments fostered by this research program or the state-of-the-art results presented during the conclusive conference. The volume covers current research in the areas of operator theory and dynamical systems on networks and their applications, indicating possible future directions. The book will be interesting to researchers focusing on the mathematical theory of networks; it is unique as, for the first time, continuous network models - a subject that has been blooming in the last twenty years - are studied alongside more classical and discrete ones. Thus, instead of two different worlds often growing independently without much intercommunication, a new path is set, breaking with the tradition. The fruitful and beneficial exchange of ideas and results of both communities is reflected in this book.

Download or read book Modularity and Dynamics on Complex Networks written by Renaud Lambiotte and published by Cambridge University Press. This book was released on 2022-02-03 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex networks are typically not homogeneous, as they tend to display an array of structures at different scales. A feature that has attracted a lot of research is their modular organisation, i.e., networks may often be considered as being composed of certain building blocks, or modules. In this Element, the authors discuss a number of ways in which this idea of modularity can be conceptualised, focusing specifically on the interplay between modular network structure and dynamics taking place on a network. They discuss, in particular, how modular structure and symmetries may impact on network dynamics and, vice versa, how observations of such dynamics may be used to infer the modular structure. They also revisit several other notions of modularity that have been proposed for complex networks and show how these can be related to and interpreted from the point of view of dynamical processes on networks.

Download or read book A Field Guide to Dynamical Recurrent Networks written by John F. Kolen and published by John Wiley & Sons. This book was released on 2001-01-15 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.

Download or read book Fundamentals Of Network Biology written by Zhang Wenjun and published by World Scientific. This book was released on 2018-05-16 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the first comprehensive title on network biology, this book covers a wide range of subjects including scientific fundamentals (graphs, networks, etc) of network biology, construction and analysis of biological networks, methods for identifying crucial nodes in biological networks, link prediction, flow analysis, network dynamics, evolution, simulation and control, ecological networks, social networks, molecular and cellular networks, network pharmacology and network toxicology, big data analytics, and more. Across 12 parts and 26 chapters, with Matlab codes provided for most models and algorithms, this self-contained title provides an in-depth and complete insight on network biology. It is a valuable read for high-level undergraduates and postgraduates in the areas of biology, ecology, environmental sciences, medical science, computational science, applied mathematics, and social science. Contents: Mathematical Fundamentals: Fundamentals of Graph TheoryGraph AlgorithmsFundamentals of Network TheoryOther FundamentalsCrucial Nodes/Subnetworks/Modules, Network Types, and Structural Comparison: Identification of Crucial Nodes and Subnetworks/ModulesDetection of Network TypesComparison of Network StructureNetwork Dynamics, Evolution, Simulation and Control: Network DynamicsNetwork Robustness and Sensitivity AnalysisNetwork ControlNetwork EvolutionCellular AutomataSelf-OrganizationAgent-based ModelingFlow Analysis: Flow/Flux AnalysisLink and Node Prediction: Link Prediction: Sampling-based MethodsLink Prediction: Structure- and Perturbation-based MethodsLink Prediction: Node-Similarity-based MethodsNode PredictionNetwork Construction: Construction of Biological NetworksPharmacological and Toxicological Networks: Network Pharmacology and ToxicologyEcological Networks: Food WebsMicroscopic Networks: Molecular and Cellular NetworksSocial Networks: Social Network AnalysisSoftware: Software for Network AnalysisBig Data Analytics: Big Data Analytics for Network Biology Readership: Advanced undergraduates and graduate students and researchers in biology, ecology, pharmacology, applied mathematics, computational science, etc. Keywords: Network Biology;Network Analysis;Food Webs;Molecular Networks;Social Networks;Network Pharmacology;Link Prediction;Network Dynamics;Big Data Analytics;Software;Models;Algorithms;Nodes;LinksReview:0

Download or read book Social Networks Models of Information Influence Control and Confrontation written by Alexander G. Chkhartishvili and published by Springer. This book was released on 2018-12-30 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys the well-known results and also presents a series of original results on the mathematical modeling of social networks, focusing on models of informational influence, control and confrontation. Online social networks are intended for communication, opinion exchange and information acquisition for their members, but recently, online social networks have been intensively used as the objects and means of informational control and an arena of informational confrontation. They have become a powerful informational influence tool, particularly for the manipulation of individuals, social groups and society as a whole, as well as a battlefield of information warfare (cyberwars). This book aimed at under- and postgraduate university students as well as experts in information technology and modeling of social systems and processes.

Download or read book Discrete Networked Dynamic Systems written by Magdi S. Mahmoud and published by Academic Press. This book was released on 2020-10-22 with total page 486 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 From Worms to Wars Modeling and Controlling Networked Dynamical Systems written by Megan Jean Morrison and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks in nature regularly exhibit dynamics that are difficult to characterize due to their nonlinear nature and use of obscure control signals. These systems are often marked by low-dimensional dynamics, multiple stable fixed points or attractors, and outputs that are generated from nonlocalized network activity. We develop procedures for characterizing nonlinear dynamics in networks with transparent, low-dimensional models and controlling them using bifurcation theory. We apply these techniques to the neural network of C. elegans, Hopfield networks, and randomly generated high-dimensional dynamical systems. We show that nonlinear control may be a method by which C. elegans regulates its behavior and could be a viable control method in other systems with multiple stable fixed points. Although much focus rests on the dynamics of nodes in a network, many networks of interest, such as sociopolitical networks, possess edge dynamics in addition to node dynamics. One such network is the international system. We explore dimension reduction techniques and the governing equations for network edge dynamics in addition to node dynamics. We show how final stable states can be predicted from initial network statistics for random matrices under the influence of structural balance dynamics; this analysis is useful for understanding when assortativity in a network, which can occur due to in-group biases, will determine the factionalization that occurs in networks under structural balance dynamics. We further build a matrix dynamical systems model of sociopolitical edge dynamics with low-conflict and high-conflict stable states. We analyze the edge dynamics in a low-dimensional eigenvalue/eigenvector space and derive bifurcations for state transitions in the eigenvalue space; this is similar to our derivation of state transitions for node dynamics. Used together, data-driven discovery, dimension reduction, and bifurcation theory can be used to effectively describe, analyze, and control network dynamics.Data-driven techniques allow us to identify the dynamics governing activity in complex networks. Dimension reduction allows us to characterize high-dimensional dynamics with far fewer variables. Bifurcation theory allows us to understand how and why qualitative transitions occur in nonlinear systems. We demonstrate these techniques on several systems including toy models, random networks, the nematode C. elegans neural network, and the European international system. We hope that these strategies for building models for network dynamics and evaluating control techniques can be useful in a wider range of networks with nonlinear dynamics.

Download or read book International Conference on Theory and Application in Nonlinear Dynamics ICAND 2012 written by Visarath In and published by Springer. This book was released on 2013-12-13 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of different lectures presented by experts in the field of nonlinear science provides the reader with contemporary, cutting-edge, research works that bridge the gap between theory and device realizations of nonlinear phenomena. Representative examples of topics covered include: chaos gates, social networks, communication, sensors, lasers, molecular motors, biomedical anomalies, stochastic resonance, nano-oscillators for generating microwave signals and related complex systems. A common theme among these and many other related lectures is to model, study, understand, and exploit the rich behavior exhibited by nonlinear systems to design and fabricate novel technologies with superior characteristics. Consider, for instance, the fact that a shark’s sensitivity to electric fields is 400 times more powerful than the most sophisticated electric-field sensor. In spite of significant advances in material properties, in many cases it remains a daunting task to duplicate the superior signal processing capabilities of most animals. Since nonlinear systems tend to be highly sensitive to perturbations when they occur near the onset of a bifurcation, there are also lectures on the general topic of bifurcation theory and on how to exploit such bifurcations for signal enhancements purposes. This manuscript will appeal to researchers interested in both theory and implementations of nonlinear systems.

Download or read book Mathematics of Epidemics on Networks written by István Z. Kiss and published by Springer. This book was released on 2017-06-08 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve differential equation models or directly simulate epidemics on networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and other departments alike.

Download or read book Practical Peer to Peer Teaching and Learning on the Social Web written by Hai-Jew, Shalin and published by IGI Global. This book was released on 2021-11-19 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: On the Social Web, people share their enthusiasms and expertise on almost every topic, and based on this, learners can find resources created by individuals with varying expertise. Through this trend and the wide availability of video cameras and authoring tools, people are creating DIY resources and sharing their knowledge, skills, and abilities broadly. While these resources are increasing in availability, what has not been explored is the effectiveness of these resources, peer-to-peer teaching and learning, and how well this content prepares learners for professional roles. Practical Peer-to-Peer Teaching and Learning on the Social Web explores the efficacies of online teaching and learning with materials by peers and provides insights into what is made available for teaching and learning by the broad public. It also considers intended and unintended outcomes of open-shared learning online and discusses practical ethics in teaching and learning online. Covering topics such as learner roles and instructional design, it is ideal for teachers, instructional designers and developers, software developers, user interface designers, researchers, academicians, and students.

Download or read book Hybrid Artificial Intelligent Systems Part I written by Manuel Grana Romay and published by Springer Science & Business Media. This book was released on 2010-06-11 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 5th International Conference on Hybrid Artificial Intelligent Systems, held in San Sebastian, Spain, in June 2010.