| 时滞神经网络的指数稳定性分析 |
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| 引用本文： | 杨德刚. 时滞神经网络的指数稳定性分析[J]. 吉首大学学报(自然科学版), 2008, 29(4): 30-34 |
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| 作者姓名： | 杨德刚 |
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| 作者单位： | 重庆师范大学数学与计算机科学学院,重庆,400047 |
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| 基金项目： | 国家自然科学基金，Natural Science Foundation Project of CQ csrc，Applying Basic Research Program of Chongqing Education Committee，重庆师范大学校科研和校改项目 |
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| 摘 要： | 研究了一类时滞细胞神经网络的指数稳定性问题，利用Razumikhin定理和线性不等式技术得到新的全局指数稳定性准则.与其他方法不同之处在于，对神经网络模型的“线性化”，将神经网络模型变成一个线性时变的系统.所获的条件具有较少的保守性.最后用1个数值例子说明文中所得的结果是有效的.
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| 关 键 词： | 神经网络 时滞 指数稳定性 线性矩阵不等式 Razumikhin定理 |
Exponential Stability of Neural Networks with Time Delays |
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| YANG De-gang. Exponential Stability of Neural Networks with Time Delays[J]. Journal of Jishou University(Natural Science Edition), 2008, 29(4): 30-34 |
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| Authors: | YANG De-gang |
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| Affiliation: | (Department of Mathematics and Computer Science,Chongqing Normal University,Chongqing 400047,China) |
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| Abstract: | This paper considers the problems of global exponential stability for a general class of neural networks withtime delays,a new criterion ensuring global exponential stability is obtained by utilizing Razumikhin theorem and thelinear matrix inequality (LMI) technique. Distinct difference from other analytical approaches lies in "linearization" ofthe neural network model, by which the considered neural network model is transformed into a linear time-variant sys-tern. The obtained conditions show to be less conservative and restrictive. A numerical simulation is given to illustratethe validity of our results. |
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| Keywords: | neural networks time delays exponential stability linear matrix inequality Razumikhin theorem |
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