Numerical differentiation by radial basis functions approximation

被引：0

作者：

T. Wei

Y. C. Hon

机构：

[1] Lanzhou University,School of Mathematics and Statistics

[2] City University of Hong Kong,Department of Mathematics

来源：

Advances in Computational Mathematics | 2007年 / 27卷

关键词：

numerical differentiation; radial basis functions; Tikhonov regularization; 65D25; 45D05; 35R25;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Based on radial basis functions approximation, we develop in this paper a new com-putational algorithm for numerical differentiation. Under an a priori and an a posteriori choice rules for the regularization parameter, we also give a proof on the convergence error estimate in reconstructing the unknown partial derivatives from scattered noisy data in multi-dimension. Numerical examples verify that the proposed regularization strategy with the a posteriori choice rule is effective and stable to solve the numerical differential problem.

引用

页码：247 / 272

页数：25

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