Padua points and fake nodes for polynomial approximation: old, new and open problems

IF 1.1 Q1 MATHEMATICS Constructive Mathematical Analysis Pub Date : 2022-03-01 DOI:10.33205/cma.1070020
S. De Marchi
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Abstract

Padua points, discovered in 2005 at the University of Padua, are the first set of points on the square [−1, 1]2 that are explicitly known, unisolvent for total degree polynomial interpolation and with Lebesgue constant increasing like log2(n) of the degree. One of the key features of the Padua Points is that they lie on a particular Lissajous curve. Other important properties of Padua points are 1. In two dimensions, Padua points are a WAM for interpolation and for extracting Approximate Fekete Points and Discrete Leja sequences. 2. In three dimensions, Padua points can be used for constructing tensor product WAMs on different compacts. Unfortunately their extension to higher dimensions is still the biggest open problem. The concept of mapped bases has been widely studied (cf. e.g. [35] and references therein), which turns out to be equivalent to map the interpolating nodes and then construct the approximant in the classical form without the need of resampling. The mapping technique is general, in the sense that works with any basis and can be applied to continuous, piecewise or discontinuous functions or even images. All the proposed methods show convergence to the interpolant provided that the function is resampled at the mapped nodes. In applications, this is often physically unfeasible. An effective method for interpolating via mapped bases in the multivariate setting, referred as Fake Nodes Approach (FNA), has been presented in [38]. In this paper, some interesting connection of the FNA with Padua points and “families of relatives nodes”, that can be used as “fake nodes” for multivariate approximation, are presented and we conclude with some open problems.
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多项式逼近的Padua点和伪节点:老问题、新问题和开放问题
帕多瓦点,2005年在帕多瓦大学发现,是正方形[−1,1]2上的第一个明确已知的点集,对于总次多项式插值来说是不分离的,并且勒贝格常数像log2(n)一样增加。帕多瓦点的一个关键特征是它们位于一条特殊的利萨尤曲线上。帕多瓦点的其他重要性质是1。在二维空间中,Padua点是用于插值和提取近似Fekete点和离散Leja序列的WAM。2. 在三维空间中,Padua点可用于构造张量积wam。不幸的是,将它们扩展到更高的维度仍然是最大的开放问题。映射基的概念已经得到了广泛的研究(参见[35]和其中的参考文献),它等价于映射插值节点,然后构造经典形式的近似,而不需要重采样。映射技术是通用的,从某种意义上说,它适用于任何基,可以应用于连续的、分段的或不连续的函数甚至图像。只要在映射节点上对函数进行重采样,所提出的方法都能收敛于插值函数。在应用程序中,这通常在物理上是不可行的。在[38]中提出了一种通过映射基在多变量环境中进行插值的有效方法,称为假节点法(Fake Nodes Approach, FNA)。本文给出了FNA与Padua点和“亲属族节点”之间的一些有趣的联系,这些节点可以用作多元逼近的“假节点”,并得到了一些开放问题。
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来源期刊
Constructive Mathematical Analysis
Constructive Mathematical Analysis Mathematics-Analysis
CiteScore
2.40
自引率
0.00%
发文量
18
审稿时长
6 weeks
期刊最新文献
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