A Neural Network Diagnosis Approach for Analog Circuits View Full Text


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Article Info

DATE

1999-09

AUTHORS

Alessandra Fanni, Alessandro Giua, Michele Marchesi, Augusto Montisci

ABSTRACT

This paper presents a neural network system for the diagnosis of analog circuits and shows how the performance of such a system can be affected by the choice of different techniques used by its submodules. In particular we discuss the influence of feature extraction techniques such as Fourier Transforms, Wavelets and Principal Component Analysis. The system uses several different power supplies and as many neural networks “in parallel”. Two different algorithms that can be used to combine the candidate sets produced by each network are also presented. The system is capable of diagnosing multiple faults even if trained on single ones. More... »

PAGES

169-186

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1008376430315

DOI

http://dx.doi.org/10.1023/a:1008376430315

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1035740690


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