| Global exponential stability of interval neural networks with a fixed delay |
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| 作者姓名： | LI Chuandong LIAO Xiaofeng College of Mathematics and Physics Chongqing University Chongqing P.R. China |
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| 作者单位： | LI Chuandong 1，2，LIAO Xiaofeng 2 1College of Mathematics and Physics，Chongqing University，Chongqing 400030，P.R. China 2Department of Computer Science and Engineering，Chongqing University，Chongqing 400030，P.R. China |
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| 基金项目： | 国家自然科学基金
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the Doctorate Foundation of the Ministry of Education of China
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the Applied Basic Research Grants Committee of Science and Technology of Chongqing
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the Basic and Applied Basic Research Foundation of Chongqing University |
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| 摘 要： | 1.IntroductionConsideradelayedneural-networkmodeldescribedbythefollowingfunctionaldifferentialequations.()()()()()()11,nniiiijjjijjjijjtautwgutvgutImt===-++-+邋&1,2,,.in=K(1a)or()()()()()()ttttt=-++-+uAuWGuVGuI&,(1b)where()()()()T12,,,ntututut=轾臌uListhestatevectoroftheneuralnetwork;()12diag,,,naaa=AKisadiagonalmatrixwithpositiveentries,i.e.,0ia>;()ijnnw=Wand()ijnnv=Varetheconnectionweightmatrixanddelayedconnectionweightmatrix,re-spectively;()()()()()()()()T1122,,,nntgutgutgut轾=臌GuKde…
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| 关 键 词： | 间隔神经网络 指数健壮稳定性 线性矩阵不等式 固定延迟 Lyapunov-Krasovskii函数 |
Global exponential stability of interval neural networks with a fixed delay |
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| LI Chuandong,LIAO Xiaofeng College of Mathematics and Physics,Chongqing University,Chongqing,P.R. China.Global exponential stability of interval neural networks with a fixed delay[J].Journal of Chongqing University,2004,3(1):39-42. |
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| Authors: | LI Chuandong LIA O Xiaofeng |
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| Abstract: | The problem of the global exponential robust stability of interval neural networks with a fixed delay was studied by an approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI). The results obtained provide an easily verified guideline for determining the exponential robust stability of delayed neural networks. The theoretical analysis and numerical simulations show that the results are less conservative and less restrictive than those reported recently in the literature. |
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| Keywords: | interval neural networks exponential robust stability Lyapunov-Krasovskii functional linear matrix inequality delayed fixed interval neural networks exponential stability theoretical analysis numerical simulations show conservative recently literature results guideline problem global exponential robust stability approach functional linear matrix inequality |
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