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.
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页码：247 / 272
页数：25
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