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Global Exponential Stability of a Class of Variable Time-Delay Cellular Neural Networks

机译:一类可变时滞细胞神经网络的全局指数稳定性

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In view of variable time-delay cellular neural networks with activation function bounded and meeting the conditions of Lippschitz, the result of the global exponential stability is obtained by constructing a special Lyapunov function equality and using Lyapunov function technology and matrix inequality. The global exponential stability of variable time-delay cellular neural networks whose activation function is likewise linear function is discussed. An example and its computer simulation is given to prove the effectiveness of the obtained result. Finally the result of this paper is discussed by comparing existing achievements, and it is with advantage of low dimension validated matrix, simple calculation and easy computer implementation.
机译:针对激活函数有界且满足Lippschitz条件的可变时滞细胞神经网络,通过构造特殊的Lyapunov函数等式,并利用Lyapunov函数技术和矩阵不等式,获得全局指数稳定性的结果。讨论了其激活函数同样为线性函数的可变时滞细胞神经网络的全局指数稳定性。通过算例和计算机仿真验证了所得结果的有效性。最后,通过比较已有的成果讨论了本文的结果,它具有低维验证矩阵,计算简单和易于计算机实现的优点。

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