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Exponential Synchronization for Neutral-Type Neural Network with Stochastic Perturbation and Markovian Jumping Parameters

机译:具有随机摄动和马尔可夫跳跃参数的中立型神经网络的指数同步

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摘要

The problem of exponential synchronization for neutral-type neural network with stochastic perturbation and Markovian switching parameters is considered in this article. Based on Lyapunov functional method and the theory of stochastic process, the exponential synchronism of the neural network is analyzed. By designing an adaptive state feedback controller, the exponential synchronization criterion of the neural network is obtained which can be represented as linear matrix inequality. Furthermore, the update rule for the adaptive controller is obtained. Finally, a simulation example is proposed to explain the availability of the results and method obtained in this article.
机译:本文考虑具有随机扰动和马尔可夫切换参数的中立型神经网络的指数同步问题。基于Lyapunov泛函方法和随机过程理论,分析了神经网络的指数同步性。通过设计自适应状态反馈控制器,获得了神经网络的指数同步准则,该准则可以表示为线性矩阵不等式。此外,获得用于自适应控制器的更新规则。最后,提出了一个仿真实例来说明本文所获得的结果和方法的可用性。

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