带有两个时滞的不确定神经网络的渐近稳定性分析  

Asymptotically stability analysis of uncertain neural networks with two time delays

作　　者：吴文娟[1] 刘德友[1] 刘海涛[1] 张静文[1] 

机构地区：[1]燕山大学理学院,秦皇岛066004

出　　处：《黑龙江大学自然科学学报》2012年第4期480-484,共5页Journal of Natural Science of Heilongjiang University

基　　金：国家自然科学基金资助项目(70671088;71071133)

摘　　要：研究一类具有两个时滞和不确定性神经网络的全局渐近稳定性问题,通过构造新的Lyapunov函数,运用线性矩阵不等式理论将T-S模糊模型扩展到带有两个时滞的含有不确定项模糊神经网络,并给出系统稳定的充分条件。仿真实例验证了结论的有效性。The global asymptotic stability of fuzzy Hopfield neural networks with uncertain parameters and time - varying delays were investigated. By framing Lyapunov function and using linear matrix inequality （LMI） theory, the T- S fuzzy model representation is extended to the stability analysis for uncertain fuzzy neural networks with two time delays. The sufficient conditions for system stability are given. Some numerical examples are given to illustrate theoretically the effectiveness of the method proposed.

关 键 词：T—S模糊模型 全局渐近稳定 不确定性 线性矩阵不等式 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]