ROBUST STABILITY CRITERIA FOR DISCRETE-TIME NEURAL NETWORKS WITH MODE-DEPENDENT TIME DELAYS AND MARKOVIAN JUMP PARAMETERS

摘要：

In this paper, we investigate the time-delay dependent robust stability problem for discrete-time neural networks with mode-dependent time delays. The jumping parameters are considered as discrete-time, discrete-state Markov process. The delay factor depends on the mode of operation. The linear factional uncertainty is considered, which means that less conservative results is obtained than using norm-bounded parameter uncertainties. All the results are cast into convenient linear matrix inequality(LMIs)forms. A numerical example is given to illustrate the effectiveness of the results.

关键词： Robust stability Discrete-time neural networks linear matriz inequalities (LMIs)

作者: XIAO-DONG ZHAO LI LI CHUN-E ZHANG

作者单位: Hebei University of Technology, Tianjin, China Hebei University of Science and Technology, Shijiazhu Hebei University of Science and Technology, Shijiazhuang 050018, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 820-823

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）