期刊
APPLIED MATHEMATICS AND COMPUTATION
卷 393, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2020.125811
关键词
Numerical differentiation; Ill posed problem; Super order Tikhonov regularization; Legendre approximation; Discrepancy principle
资金
- project of enhancing school with innovation of Guangdong ocean university [Q18306]
The paper introduces a method based on Legendre expansion to calculate numerical derivatives of a function from perturbed data, utilizing Tikhonov regularization and a new penalty term to address the ill-posedness of the problem. It has been demonstrated that the solution process is consistent across various levels of function smoothness. Additionally, self-adaptive convergence rates can be achieved by selecting the regularization parameter through a discrepancy principle. Numerical tests indicate that the method produces satisfactory results.
The aim of this paper is to develop a method based on Legendre expansion to compute numerical derivatives of a function from its perturbed data. The Tikhonov regularization combined with a new penalty term is used to deal with the ill posed-ness of the problem. It has been shown that the solution process is uniform for various smoothness of functions. Moreover, the convergence rates can be obtained self-adaptively when we choose the regularization parameter by a discrepancy principle. Numerical tests show that the method gives good results. (C) 2020 Elsevier Inc. All rights reserved.
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