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arXiv 2407.03327math.NAcs.NA
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二元函数高阶混合导数的最优方法

An optimal method for high order mixed derivatives of bivariate functions

Y. V. Semenova, S. G. Solodky

AI总结:

本文研究有限光滑性二元函数高阶混合导数的最优恢复问题,提出基于截断方法的数值微分算法,并证明其在精度和Galerkin信息量方面均达到阶最优。

摘要:

研究了具有有限光滑性的二元函数高阶混合导数的最优恢复问题。基于截断方法,构造了一种数值微分算法,该算法在精度意义和所涉及的Galerkin信息量方面都是阶最优的。提供了数值例子以说明我们的方法能够被成功实现。

英文摘要:

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.

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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