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arXiv 1407.3291math.NAcs.NA
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中等维度下总次数多项式插值的最优点集

Optimal Point Sets for Total Degree Polynomial Interpolation in Moderate Dimensions

Florida State University(佛罗里达州立大学)

Max Gunzburger, Aretha L Teckentrup

AI总结:

研究中等维度下总次数多项式插值的最优点集选择,提出计算最优插值点的新算法,分析最小勒贝格常数随多项式次数和维度的增长情况,报告最高维度下单位立方体和单位球的最小勒贝格常数值。

摘要:

本文关注中等维度下总次数多项式插值的拉格朗日插值问题。我们致力于确定插值问题中的最优点集,定义最优插值点为使勒贝格常数最小的点集。我们提出了一种新的数值算法来计算最优点的位置,该算法不依赖于域的形状,也不需要使用范德蒙德矩阵。我们进行了多项式次数和维度下最小勒贝格常数增长的数值研究,并报告了迄今为止在单位立方体和单位球中最高维度下的最小勒贝格常数值。

英文摘要:

This paper is concerned with Lagrange interpolation by total degree polynomials in moderate dimensions. In particular, we are interested in characterising the optimal choice of points for the interpolation problem, where we define the optimal interpolation points as those which minimise the Lebesgue constant. We give a novel algorithm for numerically computing the location of the optimal points, which is independent of the shape of the domain and does not require computations with Vandermonde matrices. We perform a numerical study of the growth of the minimal Lebesgue constant with respect to the degree of the polynomials and the dimension, and report the lowest values known as yet of the Lebesgue constant in the unit cube and the unit ball in up to 10 dimensions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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