An Optimal Method for High-Order Mixed Derivatives of Bivariate Functions

IF 1 4区数学 Q3 MATHEMATICS, APPLIED

Computational Methods in Applied Mathematics Pub Date : 2024-01-01 DOI:10.1515/cmam-2023-0137

Evgeniya V. Semenova, Sergiy G. Solodky

引用次数: 0

Abstract

The problem of optimal recovering high-order mixed derivatives of bivariate functions with finite smoothness is studied. Based on the truncation method, an algorithm for numerical differentiation is constructed, which is order-optimal both in the sense of accuracy and in terms of the amount of involved Galerkin information. Numerical examples are provided to illustrate the fact that our approach can be implemented successfully.

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双变量函数高阶混合导数的最优方法

研究了有限平稳性双变量函数高阶混合导数的优化恢复问题。基于截断法，构建了一种数值微分算法，该算法在精度和所涉及的 Galerkin 信息量方面都是阶次最优的。我们提供了数值示例来说明我们的方法可以成功实施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational Methods in Applied Mathematics MATHEMATICS, APPLIED-

CiteScore

2.40

自引率

7.70%

发文量

期刊介绍： The highly selective international mathematical journal Computational Methods in Applied Mathematics　(CMAM) considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs. CMAM seeks to be interdisciplinary while retaining the common thread of numerical analysis, it is intended to be readily readable and meant for a wide circle of researchers in applied mathematics. The journal is published by De Gruyter on behalf of the Institute of Mathematics of the National Academy of Science of Belarus.