A Comparison Study on Shape Parameter Selection in Pattern Recognition by Radial Basis Function Neural Networks-Reference-Cited by-同舟云学术

A Comparison Study on Shape Parameter Selection in Pattern Recognition by Radial Basis Function Neural Networks

Published:2021-05-01 Issue:1 Volume:1921 Page:012124
ISSN:1742-6588
Container-title:Journal of Physics: Conference Series
language:
Short-container-title:J. Phys.: Conf. Ser.

Author:

Tavaen S,Kaennakham S

Abstract

Abstract This study investigates three choices of shape parameter selection when the so-called Radial Basis Function (RBF) is used. Under the problem of pattern recognition via RBF-Neural Network using RC-algorithm, three RBFs are focussed on; Gaussian (GA), Multiquadric (MQ), and Compactly-Supported (CS1). Two pattern recognition cases are tested and the best choice of shape parameter is validated using Model-Selection Criteria (MSC).

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Link

https://iopscience.iop.org/article/10.1088/1742-6596/1921/1/012124/pdf

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