Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

A New Method for Constructing Radial Basis Function Neural Networks

Authors
Jinyan Sun1, Xizhao Wang
1Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University
Corresponding Author
Jinyan Sun
Available Online October 2007.
DOI
https://doi.org/10.2991/iske.2007.182How to use a DOI?
Keywords
Radial basis function neural network, Norm, Training error, Sensitivity
Abstract

Ignoring the samples far away from the training samples, our study team gives a new norm-based derivative process of localized generalization error boundary. Enlightened by the above research, this paper proposes a new method to construct radial basis function neural networks, which minimizes the sum of training error and stochastic sensitivity. Experimental results show that the new method can lead to simple and better network architecture

Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/iske.2007.182How to use a DOI?
Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jinyan Sun
AU  - Xizhao Wang
PY  - 2007/10
DA  - 2007/10
TI  - A New Method for Constructing Radial Basis Function Neural Networks
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1071
EP  - 1076
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.182
DO  - https://doi.org/10.2991/iske.2007.182
ID  - Sun2007/10
ER  -