Controlling synchronization patterns...
Lehnert, Judith.

 

  • Controlling synchronization patterns in complex networks[electronic resource] /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 003.75
    書名/作者: Controlling synchronization patterns in complex networks/ by Judith Lehnert.
    作者: Lehnert, Judith.
    出版者: Cham : : Springer International Publishing :, 2016.
    面頁冊數: xv, 203 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Synchronization.
    標題: Automatic control.
    標題: Physics.
    標題: Complex Networks.
    標題: Mathematical Models of Cognitive Processes and Neural Networks.
    標題: Physical Chemistry.
    標題: Vibration, Dynamical Systems, Control.
    標題: Systems Theory, Control.
    ISBN: 9783319251158
    ISBN: 9783319251134
    內容註: 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.
    摘要、提要註: 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.
    電子資源: http://dx.doi.org/10.1007/978-3-319-25115-8
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