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Revealing network topology and dynamical parameters in delay-coupled complex network subjected to random noise

机译:在随机噪声作用下揭示时滞耦合复杂网络的网络拓扑和动力学参数

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摘要

It is well known that random noise and time delay are two inherent ingredients in complex networks, whose dynamical parameters and topological structures are often unknown or uncertain. This paper will employ the techniques of impulsive control and adaptive control to infer dynamical parameters and network topology in delay-coupled complex network under circumstance noise. By constructing an appropriate adaptive-impulsive control strategy in the response network, the unknown dynamical parameters and topology structure contained in the drive network are to be accurately identified; moreover, these two networks will achieve the global exponential synchronization in mean square. Based on the comparison theorem of impulsive differential equations, the accuracy of the proposed identification strategy is rigorously proved. Finally, two examples with networks of chaotic oscillators are presented to illustrate the application of the suggested strategy. Meanwhile, numerical results indicate that our proposed scheme is robust against the impulsive gain, the update gain and the network topology.
机译:众所周知,随机噪声和时间延迟是复杂网络中的两个固有成分,其动态参数和拓扑结构通常是未知的或不确定的。本文将采用脉冲控制和自适应控制技术来推断环境噪声下延迟耦合复杂网络的动力学参数和网络拓扑。通过在响应网络中构建适当的自适应脉冲控制策略,可以准确识别驱动网络中包含的未知动态参数和拓扑结构;此外,这两个网络将实现均方的全局指数同步。基于脉冲微分方程的比较定理,严格证明了所提出识别策略的准确性。最后,给出了两个带有混沌振荡器网络的例子,以说明所建议策略的应用。同时,数值结果表明,我们提出的方案对脉冲增益,更新增益和网络拓扑具有鲁棒性。

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