Fault diagnosis of analog circuits with tolerances using artificial neural networks

Y. Deng, Y. He, Y. Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Citations (Scopus)
63 Downloads (Pure)

Abstract

This paper proposes a method for analog fault diagnosis using 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 reduce testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances.
Original languageEnglish
Title of host publicationIn: Procs of IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2000
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages292-295
ISBN (Print)0-7803-6253-5
DOIs
Publication statusPublished - 2000

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