Finite-time synchronization of switched neural networks with state-dependent switching via intermittent control
Finite-time synchronization of switched neural networks with state-dependent switching via intermittent control
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DOI：
10.1016/j.neucom.2019.12.031
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发表时间：
2020-04
期刊：
影响因子：
6
通讯作者：
Yongbao Wu;Yixuan Gao;Wenxue Li
中科院分区：
文献类型：
--
作者：
Yongbao Wu;Yixuan Gao;Wenxue Li
本文讨论了状态依赖切换的切换神经网络在间歇控制下的有限时间同步问题。与以往文献不同的是，本文采用非周期间歇控制使切换神经网络实现有限时间同步。建立了一个新的微分不等式，得到了我们的主要结果。同时，基于图论和微分包含理论，提出了一个合适的李雅普诺夫函数，得到了一个判据，以确保有限时间同步的切换神经网络。对于非周期间歇控制，得到了与网络拓扑结构密切相关的收敛时间，该收敛时间不依赖于控制宽度或休止宽度。最后，通过一个数值例子说明了所得结果的有效性和可行性.
In this paper, the finite-time synchronization problem for switched neural networks with state-dependent switching under intermittent control is discussed. Different from previous literature, this paper uses aperiodically intermittent control to make switched neural networks achieve finite-time synchronization. A new differential inequality is established to get our main results. Meanwhile, based on graph theory and differential inclusions theory, a proper Lyapunov function is proposed to derive a criterion to ensure finite-time synchronization of switched neural networks. And the convergence time, closely related to the topological structure of networks, is obtained and does not rely on control widths or rest widths for aperiodically intermittent control. Finally, a numerical example is presented to illustrate the effectiveness and feasibility of our results.