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approximating theorem
相关语句
  逼近定理
     An existence and iterative approximating theorem of the minimal and maximal solutions is obtained by applying the monotone iterative technique, the cone theory and the low upper solution method which generalizes the related results in the case of linear impulse.
     利用单调迭代技巧、锥理论和上下解方法 ,得到了最小解与最大解的存在性及迭代逼近定理 . 它推广了脉冲为线性形式的相应结果
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  相似匹配句对
     Theorem.
     定理:设Ω(?)
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     Theorem C.
     定理C.
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     The approximating precision of O(h 2)is obtained.
     逼近精度为 O(h2 )
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     APPROXIMATING FUNCTION AND ITS DERIVATIVES BY NEURAL NETWORKS
     用神经网络逼近函数及其导数
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     On Approximating Bayesian Networks by Removing Arcs
     对弧进行删除的Bayes网络近似方法
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Aim\ To study the approximating capacity of a new locally recurrent neural network, and draw much more general conclusions about the nonautonomous system approximation Methods\ A new locally recurrent neural network model was explored, the approximation results were drawn by using the basic neural approximating theorem and other mathematics analyzing theory Results\ Simulation results showed the approximation results were correct and the recurrent neural network was powerful for the nonlinear dynamic...

Aim\ To study the approximating capacity of a new locally recurrent neural network, and draw much more general conclusions about the nonautonomous system approximation Methods\ A new locally recurrent neural network model was explored, the approximation results were drawn by using the basic neural approximating theorem and other mathematics analyzing theory Results\ Simulation results showed the approximation results were correct and the recurrent neural network was powerful for the nonlinear dynamic system approximation Conclusion\ It is proved that the finite time trajectories of a given n dimensional nonlinear dynamic system with a control input can be approximatd by the states of the locally recurrent network under the condition of the same input and approximate initial states

目的研究局部递归神经网络的逼近能力,为递归网络在非线性系统辨识和控制中的应用提供理论依据.方法构造一种结构简洁的局部递归网络模型,使用神经网络基本逼近定理、函数分析理论分析它在一定条件下的逼近能力.结果证明了在适当的初始条件下,通过权值训练可使递归网络输出逼近n维动态系统的有限时间轨迹.结论在适当的初始条件下,局部递归网络具有逼近非线性动态系统有限时间响应的能力,数字仿真验证了理论结果的正确性.

This paper discusses the initial value problem for second order impulsive integro differential equations with nonlinear impulse. An existence and iterative approximating theorem of the minimal and maximal solutions is obtained by applying the monotone iterative technique, the cone theory and the low upper solution method which generalizes the related results in the case of linear impulse.

讨论脉冲为非线性形式的二阶脉冲积分 -微分方程的初值问题 .利用单调迭代技巧、锥理论和上下解方法 ,得到了最小解与最大解的存在性及迭代逼近定理 .它推广了脉冲为线性形式的相应结果

 
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