Exponential synchronization for inertial coupled neural networks under directed topology via pinning impulsive control
Exponential synchronization for inertial coupled neural networks under directed topology via pinning impulsive control
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DOI：
10.1016/j.jfranklin.2019.11.032
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发表时间：
2020-02
期刊：
影响因子：
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通讯作者：
Shanshan Chen;Haijun Jiang;Binglong Lu;Zhiyong Yu
中科院分区：
文献类型：
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作者：
Shanshan Chen;Haijun Jiang;Binglong Lu;Zhiyong Yu
本文主要研究具有时变延迟的惯性耦合神经网络的指数同步问题。利用扩展的Halanay微分不等式、矩阵分解理论和平均脉冲区间方法，导出了若干充分条件。此外，从有向拓扑的角度出发，设计了钉住脉冲控制，使动态网络能够实现指数同步。最后，通过数值算例对理论结果进行了验证。
This article focuses on the exponential synchronization of inertial coupled neural networks (ICNNs) with time-varying delays. An extended Halanay differential inequality, matrix decomposition theory and the average impulsive interval approach are used to derive some sufficient conditions. Furthermore, in the view of directed topology, the pinning impulsive control is designed so that the dynamical networks can achieve the exponential synchronization. Finally, some numerical examples are given to illustrate our theoretical results.