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In approximation theory,the approximation of non-smooth function |x| is a very classical problem.

逼近论中,非光滑函数|x|的逼近问题是一个非常经典的问题。

The paper is organized as follows:In chapter 1 we give a brief review of approximation theory of operators,and present the corresponding research background.

本文由四章组成,其内容如下:第一章首先回顾了算子逼近论的发展及本文所做研究课题的进展情况,并简要介绍了本文的主要内容。第二章主要讨论了q-Bernstein算子对各种函数的逼近性质。

The study of direct and inverse theorems on the approximation of linear operators to functions in normed linear spaces is an important subject in the approximation theory. It is significant in theory and application.

线性算子对赋范线性空间中函数逼近正逆定理的研究是逼近论中重要的研究课题之一,在理论和实际应用上都具有重要的意义。

This dissertation first presents a simple introduction of some important basic problems ofoperator approximation theory,and history and research status of wavelet theory.

全文首先介绍了算子逼近理论的一些重要基本问题以及小波理论发展的历史和现状,指明了线性正多项式算子逼近收敛阶的受限性。

Several strong results on neural network approximation capability obtained in this dissertation are important in the approximation theory and applications of neural networks.

本文系统地研究了多层神经网络的非线性逼近能力,给出了多层网络可一致逼近有限维空间R〓紧集上的连续函数、无穷维函数空间紧集上的连续泛函和连续算子以及布尔函数的理论证明。

The characteristics of B|spline basis function is first discussed, based on which B|spline neural network is proved to be a universal approximator.

1引言对于一个给定的非线性函数,我们都知道用神经网络可以以任意的精度来逼近它,原因就是神经网络是全局逼近器[1]。

Using the RBF neural network approximator, the main assumption of the first approach is that the minimal approximation errors satisfy certain bounding conditions.

利用RBF神经网络逼近器,第一种方法主要的假设是最小逼近误差满足确定有界条件。

A new generalized fuzzy hyperbolic model is proposed, which can be seen as the generalization of common fuzzy hyperbolic model. The generalized fuzzy hyperbolic model is proven to be a universal approximator. Two identification algorithms are put forward to identify the model from input/out data.

通过对模糊双曲正切模型的改进,提出一种广义模糊双曲正切模型,证明了此模型可以以任意精度逼近紧集上的连续非线性函数,即此模型具有全局逼近性,并给出其辨识算法。

This algorithm firstly translates arbitrary parameter curves into the piecewise cubic-degree Bezier curves, then using the properties of Bezier curve we can get the tangent vector and the normal vector of every point on the approximation curve, and calculate the approximating offset curve.

此算法先将任意形式的参数曲线转化成分段三次Bézier曲线,利用Bézier曲线的性质容易得到逼近曲线的切向量和法向量,从而计算出其等距逼近曲线。

The structrual characterizations of symmetric arrowhead matrices are discussed and the general expressions of solutions are obtained.

并且还讨论了相应的最佳逼近问题,给出了最佳逼近解的表达式及求解的数值算法和算例。

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