Ezponential Stability Analysis for Impulsive Neural Networks with Time-varying Delays

摘要：

The main purpose of this paper is to further investigate the stability problem of impulsive neural networks with time-varying delays in the case that the underlying continuous delayed neural networks are unstable. By establishing an impulsive delayed differential inequality, some novel and less conservative criteria for global exponential stability of the equilibrium point of such model are derived analytically. It is shown that under certain conditions, impulses can make the underlying continuous unstable delayed neural networks globally exponentially stable. Our results have improved and generalized some published results and are help to design stability of neural networks when both delay effect and impulsive effect axe taken into consideration. An example is also given to show the effectiveness of our results.

关键词： Global ezponential stability Impulsive Neural networks Time-varying delays

作者: Shui-Ming Cai Feng-Dan Xu Wei-Xing Zheng Zeng-Rong Liu

作者单位: Department of Mathematics,Shanghai University,Shanghai 200444,China Institute of System Biology,Shan School of Computing and Mathematics,University of Western Sydney,Australia

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 81-88

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）