Fault Diagnosis of Nonlinear Analog Circuits Using Neural Networks with Wavelet and Fourier Transforms as Preprocessors

A neural-network based analog fault diagnostic system is developed for nonlinear circuits. This system uses wavelet and Fourier transforms, normalization and principal component analysis as preprocessors to extract an optimal number of features from the circuit node voltages. These features are then...

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Veröffentlicht in:	Journal of electronic testing 2001-12, Vol.17 (6), p.471
Hauptverfasser:	Aminian, Farzan, Aminian, Mehran
Format:	Artikel
Sprache:	eng
Schlagworte:	Fault diagnosis Fourier transforms Neural networks Principal components analysis Studies
Online-Zugang:	Volltext
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