The Shape Parameter in the Shifted Surface Spline—A Sharp and Friendly Approach

Author:

Luh Lin-Tian1ORCID

Affiliation:

1. Department of Data Science, Providence University, Shalu, Taichung 43301, Taiwan

Abstract

This is a continuation of our previous study on the shape parameter contained in the shifted surface spline. We insist that the data points be purely scattered without meshes and the domain can be of any shape when conducting function interpolation by shifted surface splines. We also endeavor to make our approach easily accessible for scientists, not only mathematicians. However, the space of interpolated functions is smaller than that used before, leading to sharper function approximation. This function space has particular significance in numerical partial differential equations, especially for equations whose solutions lie in Sobolev space. Although the Fourier transform is deeply involved, scientists without a background in Fourier analysis can easily understand and use our approach.

Funder

Providence University

Publisher

MDPI AG

Reference15 articles.

1. Luh, L.-T. (2022). The Shape Parameter in the shifted surface Spline—An Easily Accessible Approach. Mathematics, 10.

2. Abramowitz, M., and Segun, I.A. (1970). Handbook of Mathematical Functions, Dover Publications, Inc.

3. Wendland, H. (2005). Scattered Data Approximation, Cambridge University Press.

4. Buhmann, M. (2003). Radial Basis Functions: Theory and Implementations, Cambridge University Press.

5. Multivariate Interpolation and Conditionally Positive Definite Function;Madych;Approx. Theory Appl.,1988

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