插值多项式在一重积分Wiener空间下的同时逼近平均误差

本文在加权L_p范数逼近意义下确定了基于第一类Chebyshev 结点组的Lagrange 插值多项式列在一重积分Wiener 空间下同时逼近平均误差的渐近阶. 结果显示在L_p范数逼近意义下Lagrange 插值多项式列的平均误差弱等价于相应的最佳逼近多项式列的平均误差. 同时, 当2≤p≤4 时,Lagrange 插值多项式列导数逼近的平均误差弱等价于相应的导数最佳逼近多项式列的平均误差. 作为对比, 本文也确定了相应的Hermite-Fejér 插值多项式列在一重积分Wiener空间下逼近的平均误差的渐近阶.     

Grünwald插值算子的Lp收敛速度

讨论了以第二类 Ｔｃｈｅｂｙｃｈｅｆｆ多项式的零点为插值结点纽的 Ｇｒǖｎｗａｌｄ 插值于Ｌ_p下 的收敛性．当１≤ｐ＜２时,给出了收敛速度的一个精确估计;当Ｐ≥２时,说明了其于Ｌ_p下不 是收敛算子列．给出了一种以第二类Ｔｃｈｅｂｙｃｈｅｆｆ多项式的零点为插值结点组的修改的 Ｇｒｕｎｗａｌｄ插值,证明了其于 Ｌ_p（１≤ｐ＜∞）下是收敛的．     

插值三角多项式在Orlicz空间逼近的渐进等式

对于具有等距分布插值结点的三角多项式,借助广义的Minkowski不等式在Orlicz空间内建立了由三角多项式逼近的渐近等式.并对于Orlicz空间内不同的函数类给出不同的结果.     

Grünwald插值算子的L2收敛性

证明了以Legendre多项式的极值点为插值结点组的Grünwald插值多项式在L2范数下是收敛的.     

Grunwald插值算子的Lp收敛速度

讨论了以第二类Tchebycheff多项式的零点为插值结点组的Grünwald插值于Lp下的收敛性.当1≤p＜2时,给出了收敛速度的一个精确估计;当p≥2时,说明了其Lp下不是收敛算子列.给出了一种以第二类Tchebycheff多项式的零点为插值结点组的修改的Grünwald插值,证明了其于Lp(1≤p＜∞)下是收敛的.     

Grünwald插值算子的加权L1收敛速度

给出了以第一类Chebyshev多项式的零点为插值结点组的Grünwald插值多项式在加权L1下收敛速度的一个估计.     

多元分次Lagrange插值

对多元多项式分次插值适定结点组的构造理论进行了深入的研究与探讨.在沿无重复分量代数曲线进行Lagrange插值的基础上,给出了沿无重复分量分次代数曲线进行分次Lagrane插值的方法,并利用这一结果进一步给出了在R~2上构造分次Lagrange插值适定结点组的基本方法.另外,利用弱Gr(o|¨)bner基这一新的数学概念,以及构造平面代数曲线上插值适定结点组的理论,进一步给出了构造平面分次代数曲线上分次插值适定结点组的方法,从而基本上弄清了多元分次Lagrange插值适定结点组的几何结构和基本特征.     

一种修正的拟Grünwald插值在Orlicz空间内的逼近度

修正了以第二类Chebyshev多项式的零点为插值结点组的拟Grünwald插值多项式,使之转化为积分形式,并利用不等式技巧和Hardy-Littlewood极大函数的方法,研究了此积分型拟Grünwald插值算子在带权Orlicz空间内的逼近问题,得出了意义相对广泛的逼近度估计的结果.     

Stieltjes-Newton型有理插值

Stieltjes型分叉连分式在有理插值问题中有着重要的地位，它通过定义反差商和混合反差商构造给定结点上的二元有理函数，我们将Stieltjes型分叉连分式与二元多项式结合起来，构造Stieltje- Newton型有理插值函数，通过定义差商和混合反差商，建立递推算法，构造的Stieltjes-Newton型有理插值函数满足有理插值问题中所给的插值条件，并给出了插值的特征定理及其证明，最后给出的数值例子，验证了所给算法的有效性．     

Hermite插值算子在Orlicz空间内的逼近

插值算子逼近是逼近论中一个非常有趣的问题,尤其是以一些特殊的点为结点的插值算子的逼近问题很受人们的关注.研究了以第一类Chebyshev多项式零点为插值结点的Hermite插值算子在Orlicz范数下的逼近.     

A discrete adapted hierarchical basis solver for radial basis function interpolation

In this paper we develop a discrete Hierarchical Basis (HB) to efficiently solve the Radial Basis Function (RBF) interpolation problem with variable polynomial degree. The HB forms an orthogonal set and is adapted to the kernel seed function and the placement of the interpolation nodes. Moreover, this basis is orthogonal to a set of polynomials up to a given degree defined on the interpolating nodes. We are thus able to decouple the RBF interpolation problem for any degree of the polynomial interpolation and solve it in two steps: (1) The polynomial orthogonal RBF interpolation problem is efficiently solved in the transformed HB basis with a GMRES iteration and a diagonal (or block SSOR) preconditioner. (2) The residual is then projected onto an orthonormal polynomial basis. We apply our approach on several test cases to study its effectiveness.     

The use of the stochastic arithmetic to estimate the value of interpolation polynomial with optimal degree

One of the considerable discussions in data interpolation is to find the optimal number of data which minimizes the error of the interpolation polynomial. In this paper, first the theorems corresponding to the equidistant nodes and the roots of the Chebyshev polynomials are proved in order to estimate the accuracy of the interpolation polynomial, when the number of data increases. Based on these theorems, then we show that by using a perturbation method based on the CESTAC method, it is possible to find the optimal degree of the interpolation polynomial. The results of numerical experiments are presented.     

On the Lebesgue constant of Berrut’s rational interpolant at equidistant nodes

It is well known that polynomial interpolation at equidistant nodes can give bad approximation results and that rational interpolation is a promising alternative in this setting. In this paper we confirm this observation by proving that the Lebesgue constant of Berrut’s rational interpolant grows only logarithmically in the number of interpolation nodes. Moreover, the numerical results suggest that the Lebesgue constant behaves similarly for interpolation at Chebyshev as well as logarithmically distributed nodes.     

On the Lebesgue constant of Berrut’s rational interpolant at equidistant nodes

It is well known that polynomial interpolation at equidistant nodes can give bad approximation results and that rational interpolation is a promising alternative in this setting. In this paper we confirm this observation by proving that the Lebesgue constant of Berrut’s rational interpolant grows only logarithmically in the number of interpolation nodes. Moreover, the numerical results suggest that the Lebesgue constant behaves similarly for interpolation at Chebyshev as well as logarithmically distributed nodes.     

Inherited Fuzzy Interpolation Based on the Inherited Lower-upper Factorization

In this paper, a new scheme is proposed to find the fuzzy interpolation polynomial. In this case, the nodes are crisp data and the values are fuzzy numbers. In order to obtain the interpolation polynomial, a linear system is solved with crisp coefficients matrix and fuzzy right hand side. Then, the inherited lower-upper (LU) triangular factorization and inherited interpolation are applied to solve this system. The examples illustrate the applicability, simplicity and efficiency of the proposed method.     

Lagrange插值和Hermite-Fejér插值在Wiener空间下的平均误差

在L_q-范数逼近的意义下,确定了基于Chebyshev多项式零点的Lagrange插值多项式列和Hermite-Fejér插值多项式列在Wiener空间下的p-平均误差的弱渐近阶.从我们的结果可以看出,当2≤q<∞,1≤p<∞时,基于第一类Chebyshev多项式零点的Lagrange插值多项式列和Hermite-Fejér插值多项式列的p-平均误差弱等价于相应的最佳逼近多项式列的p-平均误差.在信息基计算复杂性的意义下,如果可允许信息泛函为计算函数在固定点的值,那么当1≤p,q<∞时,基于第一类Chebyshev多项式零点的Lagrange插值多项式列和Hermite-Fejér插值多项式列在Wiener空间下的p-平均误差弱等价于相应的最小非自适应p-平均信息半径.     

Birkhoff型三角插值

1 引言 Birkhoff三角插值是近年来比较活跃的一个研究课题,涉及Birkhoff三角插值的研究文献也很多(如G.G.Lorentz~([1]),沈燮昌~([2])等综合性文章).     

Rational interpolation through the optimal attachment of poles to the interpolating polynomial

After recalling some pitfalls of polynomial interpolation (in particular, slopes limited by Markov's inequality) and rational interpolation (e.g., unattainable points, poles in the interpolation interval, erratic behavior of the error for small numbers of nodes), we suggest an alternative for the case when the function to be interpolated is known everywhere, not just at the nodes. The method consists in replacing the interpolating polynomial with a rational interpolant whose poles are all prescribed, written in its barycentric form as in [4], and optimizing the placement of the poles in such a way as to minimize a chosen norm of the error. This revised version was published online in June 2006 with corrections to the Cover Date.     

Optimal-order quadratic interpolation in vertices of unstructured triangulations

We study the problem of Lagrange interpolation of functions of two variables by quadratic polynomials under the condition that nodes of interpolation are vertices of a triangulation. For an extensive class of triangulations we prove that every inner vertex belongs to a local six-tuple of vertices which, used as nodes of interpolation, have the following property: For every smooth function there exists a unique quadratic Lagrange interpolation polynomial and the related local interpolation error is of optimal order. The existence of such six-tuples of vertices is a precondition for a successful application of certain post-processing procedures to the finite-element approximations of the solutions of differential problems. This work was supported by the grant GA ČR 103/05/0292.     

ON NEWMAN-TYPE RATIONAL INTERPOLATION TO ｜x｜ AT THE CHEBYSHEV NODES OF THE SECOND KIND

Recently Brutman and Passow considered Newman-type rational interpolation to ｜x｜ induced by arbitrary set of symmetric nodes in [-1,1] and gave the general estimation of the approximation error.By their methods one could establish the exact order of approximation for some special nodes. In the present paper we consider the special case where the interpolation nodes are the zeros of the Chebyshev polynomial of the second kind and prove that in this case the exact order of approximation is O（1/n｜nn）