郑州大学学报（理学版）2011，Vol.43Issue(4)：33-38,6.
具有混合时滞随机离散神经网络的渐近稳定性分析
Asymptotic Stability for Discrete-time Stochastic Neural Networks with Mixed Time-delays
摘要
Abstract
A class of stochastic neural networks with discrete and distributed time-varying delays was studied. By constructing a new Lyapunov-Krasovskii function, the theorem was achieved to ensure the asymptotic stability. The theorem was obtained in the form of linear matrix inequality, which could be calculated by LMI toolbox in Matlab. An example was provided to show the effectiveness of the theorem.关键词
随机神经网络/混合时滞/线性矩阵不等式/渐近稳定性Key words
stochastic neural network/ mixed time-delay/ linear matrix inequality/ asymptotic stability分类
信息技术与安全科学引用本文复制引用
陈一鸣,徐增辉,赵所所,周志全..具有混合时滞随机离散神经网络的渐近稳定性分析[J].郑州大学学报（理学版）,2011,43(4):33-38,6.基金项目
河北省自然科学基金资助项目,编号E2009000365. （）
