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Mean square exponential stability of stochastic delay cellular neural networks

机译:随机时滞细胞神经网络的均方指数稳定性

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By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new simple sufficient condition is presented for the exponential stability of stochastic cellular neural networks with discrete delays. The condition contains and improves some of the previous results in the earlier references. These sufficient conditions only including those governing parameters of SDCNNs can be easily checked by simple algebraic methods. Finally, one example is given to demonstrate that the proposed criteria are useful and effective.
机译:通过构造合适的Lyapunov泛函并结合矩阵不等式技术,为具有离散时滞的随机细胞神经网络的指数稳定性提出了一个新的简单充分条件。该条件包含并改进了早期参考文献中的某些先前结果。这些足够的条件(仅包括SDCNN的控制参数)可以通过简单的代数方法轻松检查。最后,通过一个例子说明所提出的标准是有用和有效的。

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