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《Control and Decision》 2009-03
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Robust stability for a class of Cohen-Grossberg neural networks by dividing delay interval

LIU Zhen-weia,b,ZHANG Hua-guanga,b,ZHANG Qing-lingc(a.Key Laboratory of Integrated Automation for the Process Industry,Ministry of Education,b.College of Information Science and Engineering,c.College of Science,Northeastern University,Shenyang 110004,China.)  
Robust stability of a class of Cohen-Grossberg neural networks with time-varying delay and parameter uncertainty is studied.An idea of dividing delay interval is used.New robust stability criteria based on this idea is derived by construsting a new Lyapunov functional.Moreover,the restriction of the time derivative of time-varying delay is released in the proposed criteria.The simulation result verifies the effectiveness of the proposed criteria.
【Fund】: 国家自然科学基金项目(60774048 60728307);; 教育部高校博士点基金项目(20070145015);; 高等学校学科创新引智计划项目(B08015);; 辽宁省自然科学基金项目(20062018)
【CateGory Index】: TP183
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