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  4. On the selection of a better radial basis function and its shape parameter in interpolation problems
 
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On the selection of a better radial basis function and its shape parameter in interpolation problems

Journal
Applied Mathematics and Computation
Journal Volume
442
Date Issued
2023-04-01
Author(s)
CHUIN-SHAN CHEN  
Noorizadegan, Amir
Young, Der-Liang  
Chen, C. S.
DOI
10.1016/j.amc.2022.127713
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/630503
URL
https://api.elsevier.com/content/abstract/scopus_id/85143794988
Abstract
A traditional criterion to calculate the numerical stability of the interpolation matrix is its standard condition number. In this paper, it is observed that the effective condition number (κeff) is more informative than the standard condition number (κ) in investigating the numerical stability of the interpolation problem. While the κeff considers the function to be interpolated, the standard condition number only depends on the interpolation matrix. We propose using the shape parameter corresponding to the maximum κeff to obtain a small error in RBF interpolation. It is also observed that the κeff helps to predict the error behavior with respect to the type of the RBF, where the basis function with a higher effective condition number yields a smaller error. In the end, we conclude that the effective condition number links to the error with respect to the selection of a radial basis function, choosing its shape parameter, number of collocation points, and test function. To this end, ten test functions are interpolated using the multiquadric, Matern family, and Gaussian basis functions to show the advantage of the proposed method.
Subjects
Better kernel function | Effective condition number | Interpolation | Radial basis functions | Shape parameter
Publisher
ELSEVIER SCIENCE INC
Type
journal article

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