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含分布时滞的随机Cohen-Grossberg神经网络的p阶指数稳定性 被引量：1

p-th Moment Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Distributed Delays
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摘要 一类含分布时滞的随机Cohen-Grossberg神经网络模型的稳定性被讨论.通过运用Razumikin定理和不等式技巧,该网络平凡解p阶指数稳定性的充分条件被建立.通过一个例子,说明结果的有效性. In this paper, the p-th moment exponential stability of stochastic Cohen-Grossberg neural networks with distributed delays is discussed. Based on the Razumikin-type theorem and inequality techniques, some sufficient conditions are derived to ensure the p-th moment exponential stability of the system. A numerical example is given to illustrate the effectiveness of the results.
作者 杜启凤 李树勇 赵亮 张秀英
机构地区 四川师范大学数学与软件科学学院
出处 《四川师范大学学报（自然科学版）》 CAS CSCD 北大核心 2013年第1期7-13,共7页 Journal of Sichuan Normal University（Natural Science）
基金 国家自然科学基金(11271270) 四川省应用基础研究项目(2009JY0066) 四川省教育厅重点科研项目(10ZA125) 高等学校博士点学科专项科研基金(20105134110001)资助项目
关键词 随机Cohen-Grossberg神经网络 分布时滞 Razumikin定理 p阶指数稳定性 stochastic Cohen-Grossberg neural networks distributed delays Razumikin-type theorem p-th moment exponential stability
分类号 O175.26 [理学—数学]
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参考文献13

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同被引文献15

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四川师范大学学报（自然科学版）
2013年 第1期

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