ON THE EFFICIENCY OF THE ORTHOGONAL LEAST-SQUARES TRAINING METHOD FORRADIAL BASIS FUNCTION NETWORKS

Authors
SHERSTINSKY A PICARD RW
Citation
A. Sherstinsky et Rw. Picard, ON THE EFFICIENCY OF THE ORTHOGONAL LEAST-SQUARES TRAINING METHOD FORRADIAL BASIS FUNCTION NETWORKS, IEEE transactions on neural networks, 7(1), 1996, pp. 195-200
Citations number
26
Categorie Soggetti
Computer Application, Chemistry & Engineering","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence","Computer Science Hardware & Architecture","Computer Science Theory & Methods
Journal title
IEEE transactions on neural networks → ACNP
ISSN journal
10459227
Volume
7
Issue
1
Year of publication
1996
Pages
195 - 200
Database
ISI
SICI code
1045-9227(1996)7:1<195:OTEOTO>2.0.ZU;2-W
Abstract
The efficiency of the orthogonal least squares (OLS) method for traini ng approximation networks is examined using the criterion of energy co mpaction. We show that the selection of basis vectors produced by the procedure is not the most compact when the approximation is performed using a nonorthogonal basis. Hence, the algorithm does not produce the smallest possible networks for a given approximation error. Specific examples are given using the Gaussian radial basis functions (RBF's) t ype of approximation networks.