DocumentCode :
2302080
Title :
A weight value initialization method for improving learning performance of the backpropagation algorithm in neural networks
Author :
Shimodaira, Hiroshi
Author_Institution :
Nihon MECCS Co. Ltd., Tokyo
fYear :
1994
fDate :
6-9 Nov 1994
Firstpage :
672
Lastpage :
675
Abstract :
In this paper, we propose a new method (the OIVS method) for initializing weight values, which is based on the equations representing the characteristics of the information transformation mechanism of a node. Numerical simulations show that the learning performance of the OIVS method is superior to that of the conventional method. It should be noted that if we use appropriate values of the parameters in the OIVS method, the nonconvergence case can be avoided
Keywords :
backpropagation; neural nets; numerical analysis; backpropagation; information transformation mechanism; learning performance; neural networks; node; numerical simulation; optimal initial value setting method; weight value initialization; Backpropagation algorithms; Equations; Multi-layer neural network; Neural networks; Numerical simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-8186-6785-0
Type :
conf
DOI :
10.1109/TAI.1994.346429
Filename :
346429
Link To Document :
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