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具有混合时滞的随机反应扩散神经网络指数稳定性 被引量：1

Exponential Stability of Stochastic Reaction-diffusion Neural Networks with Mixed Time Delays
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摘要 当电子在一个非均匀的电磁场中运动时,扩散现象不可避免的存在,因此在研究神经网络动态性能时还需要考虑状态空间随时间的变化.本文研究了一类具有混合时滞的随机反应扩散模糊细胞神经网络p阶矩指数稳定性问题.通过构造恰当的Lyapunov泛函并利用一些不等式分析技巧,得到了依赖于扩散系数的p阶矩指数稳定性充分条件.分析所得结果可发现较大的扩散系数更有利于系统实现稳定. The reaction-diffusion effects can not be avoided in the neural networks, especially when electrons are moving in asymmetric electromagnetic fields. Hence, we must take account of the states of neural networks varying in space as well as in time when we investigate the dynamical behavior of neural networks. In this paper, we consider the problem of pth moment exponential stability for a class of stochastic reaction-diffusion fuzzy cellular neural networks with mixed time delays. Also we derive the sufficient criterion dependent on diffusion coefficients to guarantee the pth moment exponential stability of equilibrium solution by constructing a suitable Lyapunov functional and utilizing some inequality techniques. The results show that the large diffusion coefficients are beneficial to the realization of exponential stability.
作者 耿立杰 李海颖 张晓静 苏广
机构地区 军械工程学院基础部 邢台学院数学与信息技术学院
出处 《工程数学学报》 CSCD 北大核心 2014年第5期687-696,共10页 Chinese Journal of Engineering Mathematics
基金 国家自然科学基金(11071254)~~
关键词 模糊细胞神经网络 反应扩散 指数稳定性 fuzzy celluar neural networks reaction-diffusion exponential stability
分类号 O175 [理学—基础数学] TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献10

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二级参考文献10

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  • 10张子芳,徐道义,邓谨.随机时滞反应扩散神经网络的指数稳定性[J].工程数学学报,2008,25(2):219-223. 被引量：4

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工程数学学报
2014年 第5期

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