NDLI: Fault diagnosis for a delta-sigma converter by a neural network

Content Provider	IEEE Xplore Digital Library
Author	Jervis, B.W. Holding, J.M.
Copyright Year	2004
Description	Author affiliation: Appl. Electron. Reasearch Group, Sheffield Univ., UK (Jervis, B.W.; Holding, J.M.)
Abstract	The diagnosis of faults in a first order /spl Delta/-/spl sigma/converter is described. The circuit behaviour of fault-free circuits and circuits containing single faults were simulated and characterized by the output bitstream patterns. The latter were compared with that of the ideal fault-free circuit. A Simplified fuzzy ARTMAP was trained with metrics derived from the bitstreams and their assigned class. A diagnostic accuracy of 93% was achieved using just two of the metrics. The technique might be useful for the diagnosis of other circuits.
Sponsorship	IEEE IEEE Finland Section IEEE SP/CAS Chapter, Finland EURASIP UCSB Tampere Univ. of Technol. Ecole Superieure des Sciences et Techniques de Tunis, ESSTT, Univ. of Manouba
Starting Page	861
Ending Page	864
File Size	344990
Page Count	4
File Format	PDF
ISBN	0780383796
DOI	10.1109/ISCCSP.2004.1296582
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-03-21
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Art Low pass filters Neural networks Voltage Artificial neural networks Circuit faults Circuit testing Signal to noise ratio Flip-flops
Content Type	Text
Resource Type	Article

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Fault diagnosis for a delta-sigma converter by a neural network