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解线性变分不等式的一种时滞神经网络的稳定性分析

Stability analysis for a delayed neural network to linear variational inequalities
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摘要 考虑了求解线性变分不等式的一种时滞投影神经网络.利用泛函微分方程理论和线性矩阵不等式方法,通过构造恰当的Liapunov泛函,证明了该模型解的存在唯一性,并给出了确保其全局指数稳定的延时依赖准则.对任意延时,在适当条件下证明了该模型的全局渐近稳定性.用数值实例验证了模型的性能和所得结论的正确性. A delayed projection neural network for the linear variational inequality is considered. Based on the theory of functional differential equations and linear matrix inequality （LMI） method, the existence and uniqueness of the solution of the model is proved and a delay- dependent criteria for globally exponential stability of this network is presented by constructing appropriate Liapunov functionals. Meanwhile, the global asymptotic stability of this network with free delay are also shown under mild conditions. Finally, the performance of the model and the obtained results are illustrated by some numerical examples.
作者 陈丰盈 高兴宝
机构地区 陕西师范大学数学与信息科学学院
出处 《陕西师范大学学报（自然科学版）》 CAS CSCD 北大核心 2012年第6期11-15,21,共6页 Journal of Shaanxi Normal University：Natural Science Edition
基金 国家自然科学基金资助项目(61273311 60671063)
关键词 线性变分不等式 时滞投影神经网络 全局指数稳定性 linear variational inequality delayed projection neural network globallyexponential stability
分类号 O231.2 [理学—运筹学与控制论]
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参考文献13

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陕西师范大学学报（自然科学版）
2012年 第6期

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