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

Global Learning of Neural Networks by Using Hybrid Optimization Algorithm

Authors
Yong-Hyun Cho1, Seong-Jun Hong
1School of Computer and Information Comm. Eng., Catholic Univ. of Daegu
Corresponding Author
Yong-Hyun Cho
Available Online October 2007.
DOI
10.2991/iske.2007.201How to use a DOI?
Keywords
Neural Networks, Global Learning, Stochastic Approximation, Gradient Descent, Backpropagation Algorithm
Abstract

This paper proposes a global learning of neural networks by hybrid optimization algorithm. The hybrid algorithm combines a stochastic approximation with a gradient descent. The stochastic approximation is first applied for estimating an approximation point inclined toward a global escaping from a local minimum, and then the backpropagation(BP) algorithm is applied for high-speed convergence as gradient descent. The proposed method has been applied to 8-bit parity check and 6-bit symmetry check problems, respectively. The experimental results show that the proposed method has superior convergence performances to the conventional method that is BP algorithm with randomized initial weights setting.

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
10.2991/iske.2007.201How 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  - Yong-Hyun Cho
AU  - Seong-Jun Hong
PY  - 2007/10
DA  - 2007/10
TI  - Global Learning of Neural Networks by Using Hybrid Optimization Algorithm
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1179
EP  - 1184
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.201
DO  - 10.2991/iske.2007.201
ID  - Cho2007/10
ER  -