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Exponential stability of impulsive high-order cellular neural networks with time-varying delays

机译:时变时滞脉冲高阶细胞神经网络的指数稳定性

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The paper considers the problems of global exponential stability for impulsive high-order neural networks with time-varying delays. By employing the Hardy inequality and the Lyapunov functional method, we present some new criteria ensuring exponential stability. The activation functions are not assumed to be differentiable or strictly increasing, and no assumption on the symmetry of the connection matrices is necessary. These criteria are important in signal processing and the design of networks. Moreover, we also extend the previously known results. One illustrative example is also given in the end of this paper to show the effectiveness of our results.
机译:考虑具有时变时滞的脉冲高阶神经网络的全局指数稳定性问题。通过使用Hardy不等式和Lyapunov函数方法,我们提出了一些确保指数稳定性的新标准。假设激活函数不是可微的或严格增加的,并且不需要假设连接矩阵的对称性。这些标准对于信号处理和网络设计很重要。此外,我们还扩展了先前已知的结果。本文末尾还给出了一个说明性示例,以显示我们的结果的有效性。

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