三奇次散乱点多项式自然样条插值

为解决较为复杂的三变量散乱数据插值问题,提出了一种三元多项式自然样条插值方法.在使得对一种带自然边界条件的目标泛函极小的情况下,用Hilbert空间样条函数方法,构造出了插值问题的解,并可表为一个分块三元三奇次多项式.其表示形式简单,且系数可由系数矩阵对称的线性代数方程组确定.     

用广义交互确认方法选择良好参数进行多元多项式散乱数据自然样条光顺

1．简介多元样条函数在多元逼近中发挥很大作用，已有数量相当多的综合报告和研究论文正式发表，就在1996年6月在法国召开的第三届国际曲线与曲面会议上便有不少多元样条方面的报告，不过总的感觉是仍然缺乏对噪声数据特别是散乱数据的有效光顺方法．李岳生、崔锦泰、关履泰、胡日章等讨论广义调配样条与张量积函数，并用希氏空间样条方法处理多元散乱数据样条插值与光顺，提出多元多项式自然样条，推广了相应一元的结果．我们知道，在样条光顺中有一个如何选择参数的问题，用广义交互确认方法（generalizedcross－validation，以下简称GC…     

散乱数据带自然边界条件三元多项式样条插值

为解决4维散乱数据Hermit-Birkhoff型插值问题,在使给定的目标泛极小的条件下,构造了一种带自然边界条件的三元多项式样条函数方法.研究了插值问题解的特征,存在唯一性,收敛性及误差,最后给出了一些数值算例.     

n维散乱数据带自然边界条件多元多项式样条插值

考虑n维散乱数据Hermit-Birkhoff型插值问题,在使给定的目标泛极小的条件下,构造了一种带自然边界条件的多元多项式样条函数插值方法.重点研究了插值问题解的特征,存在唯一性和构造方法,并讨论了收敛性及误差,最后给出了一些数值算例对方法进行验证.     

含退化边三角剖分下二元三次C~1样条空间的维数

<正>1二元三次一阶光滑样条函数二元样条函数空间在数值逼近、曲面拟合、有限元方法(FEM)、散乱数据插值、多元数值积分、微分和积分方程数值解、计算机辅助几何设计(CAGD)、计算机图形学、信号过程和数学模型等领域有着广泛的应用.而空间S_3~1(Δ)除了二元三次样条函数具有的计     

带形状参数控制的三次B样条曲线曲面的光顺

三次B样条曲线是一种广泛应用于计算机辅助几何设计中的非常重要的曲线.本文在以曲线的最小应变能作为衡量曲线光顺性的基础上,采用带调节控制参数的方法分别对三次B样条曲线和双三次B样条曲面进行了光顺处理.由所提供的方法以及实例可以看出,本方法可在曲线曲面光顺的基础上通过修改参数大小以达到控制曲线曲面形状的目的,且修改后的点的位置与原坏点的距离是由参数的大小控制决定的,这样就使得我们的光顺处理可以控制在数据测量的误差范围内.     

基于基样条局部逼近散乱数据拟合中的Shepard方法

本文针对散乱数据拟合的shepard方法,提出了一种局部逼近的新方法.该方法以局部三次基样条函数作为Shepard公式中的权函数,新的权函数具有良好的衰减性和二阶连续性,从而改进了传统方法的不足之处,使实际应用效果更好.     

部分函数线性变系数模型的样条估计及其应用

本文针对Tecator数据介绍一种新的模型一部分函数线性变系数模型,并基于样条估计方法得到了模型中未知系数函数的估计,同时在适当的条件下给出了系数函数估计及模型均方预测误差的收敛速度。通过数值模拟说明本文所提估计方法的有效性。最后基于该模型对Tecator数据进行了统计分析。     

STUDY OF THE SMOOTH DEGREE OF THE CLOSED C-B（E）ZIER AND B-TYPE SPLINE CURVE

本文研究了与多边形相切的样条曲线的构造方法和基本属性问题,给出了曲线光顺度的一般定义和计算方法.利用该方法对分段C-Bézier曲线、4-5-5-4次交错B-样条曲线和3阶B样条曲线的光顺度进行计算,获得了3阶B样条曲线最为光顺的结果.     

C-Bézier和B-型样条闭曲线光滑性研究

本文研究了与多边形相切的样条曲线的构造方法和基本属性问题,给出了曲线光顺度的一般定义和计算方法.利用该方法对分段C-Bézier曲线、4-5-5-4次交错B-样条曲线和3阶B样条曲线的光顺度进行计算,获得了3阶B样条曲线最为光顺的结果.     

Bivariate Polynomial Natural Spline Interpolation Algorithms with Local Basis for Scattered Data

Because of its importance in both theory and applications, multivariate splines have attracted special attention in many fields. Based on the theory of spline functions in Hilbert spaces, bivariate polynomial natural splines for interpolating, smoothing or generalized interpolating of scattered data over an arbitrary domain are constructed with one-sided functions. However, this method is not well suited for large scale numerical applications. In this paper, a new locally supported basis for the bivariate polynomial natural spline space is constructed. Some properties of this basis are also discussed. Methods to order scattered data are shown and algorithms for bivariate polynomial natural spline interpolating are constructed. The interpolating coefficient matrix is sparse, and thus, the algorithms can be easily implemented in a computer.     

加密网格点二元局部基插值样条函数

1.简介 由于在理论以及应用两方面的重要性,多元样条引起了许多人的注意([6],[7]),紧支撑光滑分片多项式函数对于曲面的逼近是一个十分有效的工具。由于它们的局部支撑性,它们很容易求值;由于它们的光滑性,它们能被应用到要满足一定光滑条件的情况下;由于它们是紧支撑的,它们的线性包有很大的逼近灵活性,而且用它们构造逼近方法来解决的系统是     

Complete spline smoothing

Summary The purpose of this paper is to develop complete spline smoothing methods from a computational point of view, culminating in efficient stable numerical algorithms. Both the univariate and bivariate (tensorproduct) cases will be treated.Supported in part by NASA Contract NAS9-16664     

Bivariate Polynomial Natural Spline Interpolation to Scattered Data

By means of the theory of spline interpolation in Hilbert spaces, the bivariate polynomial natural spline interpolation to scattered data is constructed. The method can easily be carried out on a computer, and parallelly generalized to high dimensional cases as well. The results can be used for numerical integration in higher dimensions and numerical solution of partial differential equations, and so on.     

The convergence of three spline methods for scattered data interpolation and fitting

The convergences of three L₁ spline methods for scattered data interpolation and fitting using bivariate spline spaces are studied in this paper. That is, L₁ interpolatory splines, splines of least absolute deviation, and L₁ smoothing splines are shown to converge to the given data function under some conditions and hence, the surfaces from these three methods will resemble the given data values.     

Quintic nonpolynomial spline solutions for fourth order two-point boundary value problem

In this paper, we develop quintic nonpolynomial spline methods for the numerical solution of fourth order two-point boundary value problems. Using this spline function a few consistency relations are derived for computing approximations to the solution of the problem. The present approach gives better approximations and generalizes all the existing polynomial spline methods up to order four. This approach has less computational cost. Convergence analysis of these methods is discussed. Two numerical examples are included to illustrate the practical usefulness of our methods.     

A spline smoothing homotopy method for nonconvex nonlinear programming

Homotopy methods are globally convergent under weak conditions and robust; however, the efficiency of a homotopy method is closely related with the construction of the homotopy map and the path tracing algorithm. Different homotopies may behave very different in performance even though they are all theoretically convergent. In this paper, a spline smoothing homotopy method for nonconvex nonlinear programming is developed using cubic spline to smooth the max function of the constraints of nonlinear programming. Some properties of spline smoothing function are discussed and the global convergence of spline smoothing homotopy under the weak normal cone condition is proven. The spline smoothing technique uses a smooth constraint instead of m constraints and acts also as an active set technique. So the spline smoothing homotopy method is more efficient than previous homotopy methods like combined homotopy interior point method, aggregate constraint homotopy method and other probability one homotopy methods. Numerical tests with the comparisons to some other methods show that the new method is very efficient for nonlinear programming with large number of complicated constraints.     

Convergence analysis of nonic-spline solutions for special nonlinear sixth-order boundary value problems

In this paper, we use nonic-spline polynomial method for the numerical solution of special nonlinear sixth-order two-point boundary value problems. The main idea is to use the conditions of continuity as discretization equations for the sixth-order boundary value problem. The end conditions are derived for defined spline. A new approach for convergence analysis of the presented method discussed. Some examples are solved to illustrate the applications of method, and to compare the computed results with other existing known methods.