Interpolation and Best Approximation for Spherical Radial Basis Function Networks
Joint Authors
Lin, Shaobo
Xu, Zongben
Zeng, Jinshan
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-30
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Lin, Shaobo& Zeng, Jinshan& Xu, Zongben. 2013. Interpolation and Best Approximation for Spherical Radial Basis Function Networks. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-454430
Modern Language Association (MLA)
Lin, Shaobo…[et al.]. Interpolation and Best Approximation for Spherical Radial Basis Function Networks. Abstract and Applied Analysis No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-454430
American Medical Association (AMA)
Lin, Shaobo& Zeng, Jinshan& Xu, Zongben. Interpolation and Best Approximation for Spherical Radial Basis Function Networks. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-454430
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-454430