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In simulation, with the same number of parameters, the new algorithm gets better approximation precision and less prediction error than those of the hinge-finding algorithm.

仿真实验表明,在参数个数相同的情况下,使用新模型的逼近算法在逼近精度与预测误差两方面都优于使用原模型。

The disadvantages of this method are analyzed. Based on the analyses, an improved training method for the self-organizing map neural network is proposed to reduce the approximation error.

在此基础上,进一步研究该方法的逼近性能,分析其两个不足之处,进而提出一种提高逼近性能的改进神经网络训练策略。

In this method, two fuzzy logic systems are used to approximate unknown functions, and an error compensator is designed to reduce the influence of approximation error on tracking accuracy.

针对一类非线性系统提出了间接自适应模糊控制方法,该方法用模糊逻辑系统逼近未知函数,并设计误差补偿器来减少逼近误差对跟踪精度的影响。

In the last part, we mainly introduce Prony approximation methods of exponential function.

第3部分:"Z-变换的有理数值逼近",主要介绍了Prony指数型函数逼近方法。

Since the structure self-organization and self-learning abilities of GFNN, it is different from the universal approximation theorem of FLS and BP theorem of NN.

由于GFNN的结构自组织和参数自学习能力,使得它与模糊逻辑系统中的万能逼近定理以及人工神经网络的BP逼近定理不同,GFNN不再只是一个存在性定理,它给出了GFNN的实现过程。

Using the information consistency principle, the first step of the algorithm transforms the identification problem into a constrained convex programming ,the result of which is then used ,in the second step, to approximate systems in the uncertainty set to obtain the identified nominal model based on a polynomial approximation theorem.

第一步通过信息一致性原理把辨识问题转化为受限凸规划问题,第二步利用一个多项式逼近定理在第一步结果基础上,对不确定集中的系数进行逼近,得到辨识出的名义模型。

To cousider the least,we have to establish these facts under some comparablystrong but not the most proper conditions.From [12] and [13],if we suppose thatfis Lipschitz continuous in t,then all the above conditions(H1)-(H3) canbe established to a class of approximating problems of (1)(2).So the followingtheorem can be proved by theorem 5 through approximation process.

这时,我们只好"退而求其次",在较强的"看来不是最适当的条件"下,来建立这些事实,从[12]和[13]中我们看到,只要加上"〓对t为Lipschitz连续",则对(1)(2)的逼近问题族,上述条件(H1)-(H3)都可建立起来,从而,通过逼近过程,用定理5就可得到如下的定理。

The zonal translation networks on the unit sphere is constructed with the best approximation of spherical harmonic polynomials and the Riesz means. The Jackson theorem of approximation by such kind of zonal translation is established.

借助于球调和多项式的最佳逼近多项式和Riesz平均构造出了单位球面S上的带形平移网络,并建立了球面带形平移网络对LS(上标 q中函数一致逼近的Jackson型定理。

Finaly, we introduce the Bernstein-Kantorovich quasi interpolant and study the approximation equivalent theorem with pointwise modulus (o≤λ≤1 ) in space L[0,1] and approximation equivalent theorem with Ditzian-Totik modulusin space L_[0,1](1 ≤p ≤ω).

最后,引入Bernstein-Kantorovich拟中插式,利用点态光滑模ω_~(2r)(0≤λ≤1)讨论了其在L_∞[0,1]空间的逼近等价定理和其在L_p[0,1](1≤p≤∞)空间关于模ω_ψ~(2r)的逼近等价定理。

In this paper we use pointwise modulus of smoothness to study approximation direct theorem and equivalent theorem for some linear operators and quasi-interpolant operators; Using pointwise modulus we discuss the strong converse inequality on K-functional; and using a modified weighted K-functional and weighted modulus of smoothness we study approximation with Jacobi weight on operator with non-zero first order moments.

本文利用点态光滑模ω_~(2r)来研究某些线性算子及逆中插式逼近正定理和等价定理;利用点态光滑模讨论其关于K-泛函的强逆不等式;同时利用一种改变的带权K-泛函和带权光滑模研究一阶矩不为零的算子的点态带Jacobi权逼近

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