Proposing a new learning algorithm to improve fault tolerance of neural networks

被引：0
|
作者：
Jalili-Kharaajoo, M [1 ]
机构：
[1] Azad Univ, Young Res Club, Tehran, Iran
来源：
COMPUTATIONAL SCIENCE - ICCS 2004, PT 2, PROCEEDINGS | 2004年 / 3037卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Fault tolerant neural network architecture, based on Multilayer Perceptron (MPL) is presented. We modify the conventional Back error propagation (BP) algorithm to be applied to this architecture with the least learning degradation for fault tolerant nodes. Simulation results for random s-a-0 faults demonstrating the fault tolerance improvement are presented.
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页码：717 / 721
页数：5
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