Fault diagnosis of analog circuits with tolerances using artificial neural networks

Deng, Y., He, Y. and Sun, Y. (2000) Fault diagnosis of analog circuits with tolerances using artificial neural networks. In: In: Procs of IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2000 :. Institute of Electrical and Electronics Engineers (IEEE), pp. 292-295. ISBN 0-7803-6253-5
Copy

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.
Item Type Book Section
Additional information “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”
Date Deposited 15 May 2025 16:16
Last Modified 30 May 2025 23:08

Explore Further

picture_as_pdf
904240.pdf
View Download

Atom BibTeX OpenURL ContextObject in Span OpenURL ContextObject Dublin Core MPEG-21 DIDL Data Cite XML EndNote HTML Citation METS MODS RIOXX2 XML Reference Manager Refer ASCII Citation
Export

Downloads