首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Synchronization of hybrid coupled reaction–diffusion neural networks with time delays via generalized intermittent control with spacial sampled-data
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Synchronization of hybrid coupled reaction–diffusion neural networks with time delays via generalized intermittent control with spacial sampled-data

机译:通过具有空间采样数据的广义间歇控制与时间延迟的混合耦合反作用 - 扩散神经网络的同步

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摘要

The exponential synchronization of hybrid coupled reaction–diffusion neural networks with time delays is discussed in this article. At first, a generalized intermittent control with spacial sampled-data is introduced, which is intermittent in time and data sampling in space. This type of control strategy not only can unify the traditional periodic intermittent control and the aperiodic case, but also can lower the update rate of the controller in both temporal and spatial domains. Next, based on the designed control protocol and the Lyapunov–Krasovskii functional approach, some novel and readily verified criteria are established to guarantee the exponential synchronization of the considered networks. These criteria depend on the diffusion coefficients, coupled strengths, time delays as well as control parameters. Finally, the effectiveness of the proposed control strategy is shown by a numerical example.
机译:在本文中讨论了混合耦合反作用 - 扩散神经网络的指数同步。 首先,引入具有空间采样数据的广义间歇控制,其在时间间歇性和空间中的数据采样。 这种类型的控制策略不仅可以统一传统的周期性间歇控制和非周期性情况,而且还可以降低时间和空间域中的控制器的更新率。 接下来,基于设计的控制协议和Lyapunov-Krasovskii功能方法,建立了一些新颖且易于验证的标准,以保证所考虑的网络的指数同步。 这些标准取决于扩散系数,耦合强度,时间延迟以及控制参数。 最后,通过数值示例显示了所提出的控制策略的有效性。

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