Open Access
2013 Interpolation and Best Approximation for Spherical Radial Basis Function Networks
Shaobo Lin, Jinshan Zeng, Zongben Xu
Abstr. Appl. Anal. 2013: 1-5 (2013). DOI: 10.1155/2013/206265


Within the conventional framework of a native space structure, a smooth kernel generates a small native space, and radial basis functions stemming from the smooth kernel are intended to approximate only functions from this small native space. In this paper, we embed the smooth radial basis functions in a larger native space generated by a less smooth kernel and use them to interpolate the samples. Our result shows that there exists a linear combination of spherical radial basis functions that can both exactly interpolate samples generated by functions in the larger native space and near best approximate the target function.


Download Citation

Shaobo Lin. Jinshan Zeng. Zongben Xu. "Interpolation and Best Approximation for Spherical Radial Basis Function Networks." Abstr. Appl. Anal. 2013 1 - 5, 2013.


Published: 2013
First available in Project Euclid: 27 February 2014

zbMATH: 1295.41005
MathSciNet: MR3121531
Digital Object Identifier: 10.1155/2013/206265

Rights: Copyright © 2013 Hindawi

Vol.2013 • 2013
Back to Top