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Exponential synchronization of coupled inertial neural networks with mixed delays via weighted integral inequalities
International Journal of Robust and Nonlinear Control ( IF 3.2 ) Pub Date : 2020-09-07 , DOI: 10.1002/rnc.5183
Seakweng Vong 1 , Chenyang Shi 1 , Zhongsheng Yao 1
Affiliation  

We study the exponential synchronization of coupled inertial neural networks with both discrete‐time delay and distributed delay by quantized pinning controllers. Novel integral inequalities, which generalize the Jensen‐based inequality, are developed by choosing appropriate weight functions in our recent work. An exponential synchronization criterion is established by applying these inequalities to analyzing a Lyapunov‐Krasovskii functional which takes mixed delays into account. Numerical simulations show that the criterion can reduce conservativeness when designing parameters of the controller.

中文翻译:

加权积分不等式混合时滞耦合惯性神经网络的指数同步。

我们通过量化钉扎控制器研究了具有离散时间延迟和分布式延迟的耦合惯性神经网络的指数同步。通过在我们最近的工作中选择适当的权重函数,可以开发出新的积分不等式,这些积分不等式可以推广基于詹森的不等式。通过应用这些不等式来分析考虑了混合延迟的Lyapunov-Krasovskii泛函,从而建立了指数同步准则。数值仿真表明,该准则在设计控制器参数时可以降低保守性。
更新日期:2020-10-17
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