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非线性系统稳定分析的特征函数法及其应用 被引量:3

A QUANTITATIVE CHARACTERIZATION FOR STABILITY ANALYSIS OF NONLINEAR SYSTEM AND ITS APPLICATIONS
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摘要 本文引入一个特征函数,用于定量刻画非线性常微分方程的指数稳定性.与常用的Lyapunov方法相比,该方法简单、易用,而且易获得对一族范数(所有单调范数)皆成立的稳定性条件.所获结果推广了稳定性理论中的一些著名结论,仲应用于非线性连续神经网络的指数稳定性分析,推广和深化了[1-3]所获得的基本结论. A characteristic function is introduced to quantitatively characterize the exponential stability of nonlinear ordinary differential equations. Some well-known theorems in stability theory are extended and some new results on the exponential stability of nonlinear continuous neural networks reported in [1-3] are generalized.
出处 《应用数学学报》 CSCD 北大核心 2001年第4期495-501,共7页 Acta Mathematicae Applicatae Sinica
关键词 非线性常微分方程 稳定性分析 神经网络 全局指数稳定性 局部指数稳定性 特征函数法 Nonlinear ordinary differential equation, stability analysis, neural network,global exponential stability local exponential stability
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  • 1Xu D Y,Zhao H Y,Zhu H.Global dynamics of hopfield neural networks involving variable delays[J].Computers and Mathematica with Applications,2001,42:39.
  • 2Peng J G,Qiao H,Xu Z B.A new approach to stability of neural networks with time-varying delays[J].Neural Networks,2002,15:95.
  • 3Driver R D.Ordinary and delay differential equations[M].New York:Springer-Verlag,1977.
  • 4Ortega J M,Rhcinboldt W C.Iterative solution of nonlinear equations in several variables[M].New York:Academic,1970.
  • 5Cao J D,Wang J.Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays[J].Neural Networks,2004,17:379.
  • 6廖晓昕.动力系统的稳定性理论和应用[M]国防工业出版社,2000.

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