Expenential stability of recurrent neural networks with time-varying discrete and distributed delays

摘要：

The global exponential stability of a class of recurrent neural networks (RNNs) with time-varying discrete and distributed delays is investigated. A novel delay-dependent sufficient condition is derived based on Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) technique, under a more general assumption on the activation function. Finally, A illustrate example is given to show the effectiveness of our theoretical result.

关键词： recurrent neural networks:exponential stability:linear matrix inequality:time-varying delays distributed delays

作者: Liu Yonghua Luo Wenguang

作者单位: Department of Electronic Information and Control Engineering Guangxi University of Technology Liuzhou,China

会议类型: 国际会议

会议名称: The 5th International Conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE10)

会议地点: 合肥

会议语种:英文

页码: 1668-1672

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）