DocumentCode
2748992
Title
On the application of artificial neural networks to fault diagnosis in analog circuits with tolerances
Author
Ying, Deng ; Yigang, He
Author_Institution
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Volume
3
fYear
2000
fDate
2000
Firstpage
1639
Abstract
This paper proposes a method for analog fault diagnosis by adopting neural networks. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of component tolerances and to reduce the testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network, which is shown to be capable of robust diagnosis of analog circuits with tolerances
Keywords
analogue circuits; backpropagation; circuit testing; fault diagnosis; neural nets; nonlinear network analysis; tolerance analysis; ANN; analog circuits; analog fault diagnosis; artificial backward propagation neural network; component tolerances; fault diagnosis; robust diagnosis; testing time reduction; tolerances; Analog circuits; Artificial neural networks; Circuit faults; Circuit testing; Equations; Fault diagnosis; Intelligent networks; Neural networks; Neurons; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-5747-7
Type
conf
DOI
10.1109/ICOSP.2000.893415
Filename
893415
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