期刊
CHAOS SOLITONS & FRACTALS
卷 40, 期 5, 页码 2102-2113出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2007.09.098
关键词
-
资金
- National Natural Science Foundation of China [60674092]
- High-tech R&D Program of Jiangsu (Industry) [BG2006010]
In this paper, the global robust exponential stability for a class of delayed BAM neural networks with norm-bounded uncertainty is studied. Some less conservative conditions are presented for the global exponential stability of BAM neural networks with time-varying delays by constructing a new class of Lyapunov functionals combined with free-weighting matrices, This novel approach, based oil the linear matrix inequality (LMI) technique, removes some existing restrictions on the system's parameters, and the derived conditions are easy to verify via the LMI toolbox. Comparisons between our results and previous results admit that our results establish a new set of stability criteria for delayed BAM neural networks. (C) 2007 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据