Numerical differentiation by radial basis functions approximation
Numerical differentiation by radial basis functions approximation
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DOI：
10.1007/s10444-005-9001-0
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发表时间：
2007-08
影响因子：
1.7
通讯作者：
T. Wei;B. Hon
中科院分区：
文献类型：
--
作者：
T. Wei;B. Hon
基于径向基函数逼近，本文提出了一种新的数值微分计算算法。在正则化参数的先验和后验选择规则下，给出了从多维散乱噪声数据中重构未知偏导数的收敛误差估计的证明。数值算例验证了本文提出的后验选择规则正则化策略对求解数值微分问题的有效性和稳定性。
Based on radial basis functions approximation, we develop in this paper a new com-putational algorithm for numerical differentiation. Under ana prioriand ana posteriorichoice 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 thea posteriorichoice rule is effective and stable to solve the numerical differential problem.