Soft Fault Classification of Analog Circuits Using Network Parameters and Neural Networks

A new method to identify component faults in analog circuits is proposed using network parameters like driving point impedance, transfer impedance, voltage gain and current gain. Using Monte-Carlo simulation each component of the circuit is varied within its tolerance limit and samples of each netwo...

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Veröffentlicht in:	Journal of electronic testing 2013-04, Vol.29 (2), p.237-240
Hauptverfasser:	Kavithamani, A., Manikandan, V., Devarajan, N.
Format:	Artikel
Sprache:	eng
Schlagworte:	CAE) and Design Circuits Circuits and Systems Classification Computer simulation Computer-Aided Engineering (CAD Electrical Engineering Engineering Fault diagnosis Faults Impedance Mathematical models Monte Carlo simulation Networks Neural networks
Online-Zugang:	Volltext
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