A refined first-order expansion formula in Rn: Application to interpolation and finite element error estimates

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED
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引用次数: 0

Abstract

The aim of this paper is to derive a refined first-order expansion formula in Rn, the goal being to get an optimal reduced remainder, compared to the one obtained by usual Taylor’s formula. For a given function, the formula we derived is obtained by introducing a linear combination of the first derivatives, computed at n+1 equally spaced points. We show how this formula can be applied to two important applications: the interpolation error and the finite elements error estimates. In both cases, we illustrate under which conditions a significant improvement of the errors can be obtained, namely how the use of the refined expansion can reduce the upper bound of error estimates.

Rn 中的精炼一阶扩展公式:应用于插值和有限元误差估计
本文旨在推导出 Rn 中的精炼一阶展开公式,目的是获得与通常的泰勒公式相比最优的缩减余数。对于给定函数,我们通过引入在 n+1 个等间距点计算的一阶导数的线性组合,得到了推导出的公式。我们展示了如何将此公式应用于两个重要的应用领域:插值误差和有限元误差估计。在这两种情况下,我们都说明了在哪些条件下可以显著改善误差,即使用细化展开如何降低误差估计的上限。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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