变时滞随机模糊细胞神经网络稳定性分析(英文)  

Globally Asymptotic Stability of Stochastic Fuzzy Cellular Neural Networks with Time-varying Delays

作　　者：汪菁宜 彭国强[1] 

机构地区：[1]湖南大学数学与计量经济学院,湖南长沙410082

出　　处：《经济数学》2014年第1期17-20,共4页Journal of Quantitative Economics

基　　金：国家自然科学基金重大项目(71090402);国家自然科学基金面上项目(71771095)

摘　　要：本文旨在研究一类带变时滞的随机模糊细胞神经网络的稳定性.通过构造恰当的Lyapunov泛函并运用线性矩阵不等式(LMI)理论,作者给出了保证这类神经网络全局渐近稳定的充分条件.本文推导出两个定理:一个用以判定文中模型的全局渐进稳定性,一个用以判定该模型在均方意义下的全局渐近稳定性.This paper aims at solving the problem of checking the stability of a class of stochastic fuzzy cellular neural networks with time-varying delays.By constructing suitable Lyapunov functional and applying linear matrix inequality（LMI） theory,some sufficient conditions were developed to guarantee its globally asymptotic stability of this kind of neural networks.Two main results were obtained：one considering the globally asymptotic stability of the model,the other regarding its globally asymptotic stability in the mean square.

关 键 词：随机模糊神经网络 变时滞 全局渐近稳定性 

分 类 号：O29[理学—应用数学]