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基于脉冲控制的复杂动力网络的广义同步。

Generalized synchronization of complex dynamical networks via impulsive control.

机构信息

School of Mathematics and Statistics, Wuhan University, Hubei 430072, China.

出版信息

Chaos. 2009 Dec;19(4):043119. doi: 10.1063/1.3268587.

Abstract

This paper investigates the generalized synchronization (GS) of two typical complex dynamical networks, small-world networks and scale-free networks, in terms of impulsive control strategy. By applying the auxiliary-system approach to networks, we demonstrate theoretically that for any given coupling strength, GS can take place in complex dynamical networks consisting of nonidentical systems. Particularly, for Barabasi-Albert scale-free networks, we look into the relations between GS error and topological parameter m, which denotes the number of edges linking to a new node at each time step, and find out that GS speeds up with increasing m. And for Newman-Watts small-world networks, the time needed to achieve GS decreases as the probability of adding random edges increases. We further reveal how node dynamics affects GS speed on both small-world and scale-free networks. Finally, we analyze how the development of GS depends on impulsive control gains. Some abnormal but interesting phenomena regarding the GS process are also found in simulations.

摘要

本文研究了两种典型的复杂网络(小世界网络和无标度网络)在脉冲控制策略下的广义同步(GS)。通过将辅助系统方法应用于网络,我们从理论上证明,对于任意给定的耦合强度,由非相同系统组成的复杂动力网络中可以发生 GS。特别是,对于 Barabasi-Albert 无标度网络,我们研究了 GS 误差与拓扑参数 m 之间的关系,其中 m 表示每个时间步连接到新节点的边数,并发现随着 m 的增加 GS 会加速。对于 Newman-Watts 小世界网络,随着随机边添加概率的增加,达到 GS 所需的时间减少。我们进一步揭示了节点动力学如何影响小世界和无标度网络上的 GS 速度。最后,我们分析了 GS 的发展如何取决于脉冲控制增益。在仿真中还发现了一些关于 GS 过程的异常但有趣的现象。

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