一类随机细胞神经网络的均方指数稳定性  

Mean Square Exponential Stability of a Class of Stochastic Rcellular Neural Networks

作　　者：刘新 陈丽丽 黄帅 LIU Xin;CHEN Li-li;HUANG Shuai(School of Applied Sciences,Harbin University of Science and Technology,Harbin 150080,China)

机构地区：[1]哈尔滨理工大学理学院,黑龙江哈尔滨150080

出　　处：《哈尔滨理工大学学报》2020年第5期149-157,共9页Journal of Harbin University of Science and Technology

基　　金：国家自然科学基金(11401141);黑龙江省高校青年创新人才培养计划(UNPYSCT-2017078);黑龙江省博士后科研启动基金(LBH-Q18067)。

摘　　要：讨论了一类具有传递时滞和分布时滞以及区间不确定性的脉冲随机反应-扩散细胞神经网络(CNNs)的均方指数稳定性问题。利用H9lder不等式,It8等距性质和压缩映射原理,提出了保证上述神经网络均方指数稳定的充分条件。此外,给出一个具体例子来验证所获得的结果是有效的。In this paper, the problem of the mean square exponential stability of a class of impulsive stochastic reaction-diffusion cellular neural networks(CNNs) with transmission delay and distributed delay, and parameter uncertainties is discussed. By using H9 lder inequality, It8 isometric nature and Contraction Mapping Principle, a sufficient condition to guarantee the mean square exponential stability of the above CNNs is proposed. Moreover, an example is given to demonstrate that the obtained result is effective.

关 键 词：指数稳定性 细胞神经网络 压缩映像原理 

分 类 号：O177.2[理学—数学]