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Exponential synchronization ofdiscontinuous neural networks with time-varying mixed delays via state feedback andimpulsive control

机译:的指数同步通过状态反馈和时变混合延迟的不连续神经网络冲动控制

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摘要

This paper investigates drive-response synchronization for a class of neural networks with time-varying discrete and distributed delays (mixed delays) as well as discontinuous activations. Strict mathematical proof shows the global existence of Filippov solutions to neural networks with discontinuous activation functions and the mixed delays. State feedback controller and impulsive controller are designed respectively to guarantee global exponential synchronization of the neural networks. By using Lyapunov function and new analysis techniques, several new synchronization criteria are obtained. Moreover, lower bound on the convergence rate is explicitly estimated when state feedback controller is utilized. Results of this paper are new and some existing ones are extended and improved. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.
机译:本文研究了具有时变离散和分布式延迟(混合延迟)以及不连续激活的一类神经网络的驱动响应同步。严格的数学证明表明,对于具有不连续激活函数和混合延迟的神经网络,Filippov解的全局存在。分别设计了状态反馈控制器和脉冲控制器,以保证神经网络的全局指数同步。通过使用Lyapunov函数和新的分析技术,获得了几个新的同步标准。此外,当利用状态反馈控制器时,会明确估计收敛速率的下限。本文的结果是新的,一些已有的结果得到了扩展和改进。最后,通过数值模拟验证了理论结果的有效性。

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