Exponential Stabilization of Neural Networks With Various Activation Functions and Mixed Time-Varying Delays
Exponential Stabilization of Neural Networks With Various Activation Functions and Mixed Time-Varying Delays
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DOI：
10.1109/tnn.2010.2049118
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发表时间：
2010-07
影响因子：
--
通讯作者：
V. Phat;H. Trinh
中科院分区：
文献类型：
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作者：
V. Phat;H. Trinh
本文给出了具有不同激活函数和时变连续分布时滞的神经网络全局指数镇定的一些结果。基于增广的时变Lyapunov-Krasovskii泛函，以线性矩阵不等式的形式得到了新的全局指数镇定的时滞相关条件。最后给出了一个数值算例，说明了结果的可行性。
This paper presents some results on the global exponential stabilization for neural networks with various activation functions and time-varying continuously distributed delays. Based on augmented time-varying Lyapunov-Krasovskii functionals, new delay-dependent conditions for the global exponential stabilization are obtained in terms of linear matrix inequalities. A numerical example is given to illustrate the feasibility of our results.