Interpolation and best approximation for spherical radial basis function networks
type: Item
instance of: scholarly article
title: Interpolation and best approximation for spherical radial basis function networks
zbMATH Open document ID: 1295.41005
DOI: 10.1155/2013/206265
author: Jinshan Zeng
author: Shaobo Lin
author: Zongben Xu
published in: Abstract and Applied Analysis
publication date: 2014-06-23T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 41A05
Mathematics Subject Classification ID: 41A50
zbMATH DE Number: 6306526
zbMATH Keywords: smooth radial basis functions
zbMATH Keywords: smooth kernel
Wikidata QID: Q58915545
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/206265
OpenAlex ID: W2122799173
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description: scientific article; zbMATH DE number 6306526