Learning-based on-line testing in feedforward neural networks

被引：0
|
作者：
Kamiura, N [1 ]
Yamato, K [1 ]
Isokawa, T [1 ]
Matsui, N [1 ]
机构：
[1] Himeji Inst Technol, Dept Comp Engn, Himeji, Hyogo 6712201, Japan
来源：
PROCEEDINGS OF THE EIGHTH IEEE INTERNATIONAL ON-LINE TESTING WORKSHOP | 2002年
关键词：
D O I：
10.1109/OLT.2002.1030206
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Learning-based on-line testing in feedforward neural networks (NNs) is discussed. After the convergence of the ordinary learning, the re-learning employing two sigmoid activation functions per neuron in the last layer of the NN is made. It sets up the range of erroneous potentials produced from the last layer, and enables us to detect faults without extra hardware.
引用
收藏
页码：180 / 182
页数：3
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