High order numerical derivatives for one-dimensional scattered noisy data

被引：24
|
作者：
Wei, T. [1 ]
Li, M. [1 ]
机构：
[1] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2006年 / 175卷 / 02期
关键词：
numerical derivatives; radial basis function; Tikhonov regularization;
D O I：
10.1016/j.amc.2005.09.018
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Based on the smoothing spline approximation, in this paper we propose a regularization method for computing high order numerical derivatives from one-dimensional noisy data. The convergence rates under two different choices of the regularization parameter are obtained. Numerical examples show that the proposed method is effective and stable. (c) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码：1744 / 1759
页数：16
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