论文部分内容阅读
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.
The purpose of this paper is to study 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, the authors give the guarantee of global asymptotic stability of such neural networks We derive two theorems: one to determine the global asymptotic stability of the model and one to determine the global asymptotic stability of the model in the sense of the mean.