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动态神经网络的输入-状态稳定性分析 被引量:2

Input-to-state stability analysis of dynamic neutral networks
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摘要 针对非自治的动态神经网络系统,建立了动态神经网络的数学模型,并将其等效成一个非线性仿射控制系统.深入分析了该系统平衡点的存在性、唯一性和全局渐近稳定性,给出了系统输入-状态稳定的充分条件,构建了ISS-Lyapunov函数,并应用该函数确保了系统的全局渐近稳定性. A mathematical model of dynamic neural networks is built, which is shown to be equivalent to an affine nonlinear control system. The existence and uniqueness of the equilibrium point and the global stability of dynamic neural network models for the non-autonomous case are investigated. The sufficient conditions for the input-to-state stability are provided. ISS-Lyapunov functions are constructed and employed to insure global asymptotic stability of systems.
出处 《控制与决策》 EI CSCD 北大核心 2004年第12期1391-1394,共4页 Control and Decision
关键词 动态神经网络 全局渐近稳定性 输入-状态稳定性 Mathematical models Nonlinear systems System stability Theorem proving Transfer functions
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参考文献6

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共引文献4

同被引文献23

  • 1牛健人,张子方,徐道义.变时滞Cohen-Grossberg随机神经网络的均方指数稳定性[J].工程数学学报,2005,22(6):1001-1005. 被引量:10
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