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Controlling synchronization patterns in complex networks[electronic resource] /

Record Type:	Language materials, printed : Monograph/item
[NT 15000414]:	003.75
Title/Author:	Controlling synchronization patterns in complex networks/ by Judith Lehnert.
Author:	Lehnert, Judith.
Published:	Cham : : Springer International Publishing :, 2016.
Description:	xv, 203 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
Subject:	Synchronization.
Subject:	Automatic control.
Subject:	Physics.
Subject:	Complex Networks.
Subject:	Mathematical Models of Cognitive Processes and Neural Networks.
Subject:	Physical Chemistry.
Subject:	Vibration, Dynamical Systems, Control.
Subject:	Systems Theory, Control.
ISBN:	9783319251158
ISBN:	9783319251134
[NT 15000228]:	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.
[NT 15000229]:	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.
Online resource:	http://dx.doi.org/10.1007/978-3-319-25115-8

Controlling synchronization patterns in complex networks[electronic resource] /
Lehnert, Judith.

Controlling synchronization patterns in complex networks[electronic resource] /by Judith Lehnert. - Cham :Springer International Publishing :2016. - xv, 203 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

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.

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.

ISBN: 9783319251158

Standard No.: 10.1007/978-3-319-25115-8doiSubjects--Topical Terms:

383601
Synchronization.

LC Class. No.: Q172.5.S96

Dewey Class. No.: 003.75

Controlling synchronization patterns in complex networks[electronic resource] /
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505 0 $a 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.
520 $a 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.
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