摘要
本文通过构造一种新的Lyapunov泛函,得到了时滞Cohen-Grossberg神经网络的全局渐近稳定性的充分条件,这个条件是通过线性矩阵不等式(LIM)的形式表示出来的,条件中的自由权矩阵表明本文的结论具有较小的保守性。
In this paper, via a new Lyapunov - Krasovskii functional, we propose a novel sufficient condition guaranteeing a delayed Cohen- Grossberg neural networks is globally asymptotically stable. This condition is expressed in terms of linear matrix inequaliyies（LIMs）. The free - weighting matrices in the sufficient conditions are provided to show that the proposed stability result is less conservative.
出处
《数学理论与应用》
2009年第4期52-55,共4页
Mathematical Theory and Applications
基金
中国博士后基金资助(20070412990)
