Research on Fault Diagnosis Approach of Analog Circuit Based on Neural Network

被引：0
|
作者：
Liu Meirong [1 ]
Li Yun [1 ]
机构：
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
来源：
2008 INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND TRAINING AND 2008 INTERNATIONAL WORKSHOP ON GEOSCIENCE AND REMOTE SENSING, VOL 2, PROCEEDINGS, | 2009年
关键词：
D O I：
10.1109/ETTandGRS.2008.353
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
According to circuit decomposition technology and crossover tearing technology; a fast approach of module level fault diagnosis for analog circuit based on BPNN (back propagation neural network) is presented. Because the neural networks can create the fault dictionary, memorize and verify it simultaneously, computation time is drastically reduced. The new approach is based on parallel diagnosis, so fault modules can be located quickly and effectively. Two examples are given to illustrate the approach for both small and large-scale circuits.
引用
收藏
页码：785 / 788
页数：4
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