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Controlling Synchronization Patterns in Complex Networks / / by Judith Lehnert



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Autore: Lehnert Judith Visualizza persona
Titolo: Controlling Synchronization Patterns in Complex Networks / / by Judith Lehnert Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Edizione: 1st ed. 2016.
Descrizione fisica: 1 online resource (213 p.)
Disciplina: 003.75
Soggetto topico: Physics
Neural networks (Computer science)
Chemistry, Physical and theoretical
Vibration
Dynamics
System theory
Applications of Graph Theory and Complex Networks
Mathematical Models of Cognitive Processes and Neural Networks
Physical Chemistry
Vibration, Dynamical Systems, Control
Systems Theory, Control
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
Nota di contenuto: Introduction -- Complex Dynamical Networks -- Synchronization In Complex Networks -- Control of Synchronization Transitions by Balancing Excitatory and Inhibitory Coupling -- Cluster and Group Synchrony: The Theory -- Zero-Lag  and Cluster Synchrony: Towards Applications -- Adaptive Control -- Adaptive Time-Delayed Feedback Control -- Adaptive Control of Cluster States in Network Motifs -- Adaptive Topologies -- Conclusion.
Sommario/riassunto: This research aims to achieve a fundamental understanding of synchronization and its interplay with the topology of complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, medicine and engineering. Most prominently, synchronization takes place in the brain, where it is associated with several cognitive capacities but is - in abundance - a characteristic of neurological diseases. Besides zero-lag synchrony, group and cluster states are considered, enabling a description and study of complex synchronization patterns within the presented theory. Adaptive control methods are developed, which allow the control of synchronization in scenarios where parameters drift or are unknown. These methods are, therefore, of particular interest for experimental setups or technological applications. The theoretical framework is demonstrated on generic models, coupled chemical oscillators and several detailed examples of neural networks.
Titolo autorizzato: Controlling Synchronization Patterns in Complex Networks  Visualizza cluster
ISBN: 3-319-25115-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910254609803321
Lo trovi qui: Univ. Federico II
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Serie: Springer Theses, Recognizing Outstanding Ph.D. Research, . 2190-5053