NDLI: Fault diagnosis of mixed signal VLSI systems using artificial neural networks

Content Provider	IEEE Xplore Digital Library
Author	Nissar, A.I. Upadhyaya, S.J.
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Sci. & Eng., State Univ. of New York, Buffalo, NY, USA (Nissar, A.I.)
Abstract	This paper presents an approach to the diagnosis of linear and nonlinear analog circuits. The diagnosis methodology is focused on the soft faults in analog circuits. An on-chip white noise generator provides the test stimulus and an artificial neural net (ANN) is used as the response evaluator. Our analysis shows that the white noise relative to the pole zero locations of the circuit transfer function has a significant impact on the classification efficiency of ANN. White noise based stimulus method works for some nonlinear circuits as long as they are constrained to operate in their small signal region of operation. Circuits with strong nonlinearity are difficult to diagnose using the noise stimulus approach. Our results are demonstrated for a linear filter, Schmidt trigger and the phase lock loop (PLL).
Starting Page	93
Ending Page	98
File Size	507420
Page Count	6
File Format	PDF
ISBN	0780355105
DOI	10.1109/SSMSD.1999.768598
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-04-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Very large scale integration White noise Analog circuits Circuit faults Circuit testing Artificial neural networks Poles and zeros Transfer functions Nonlinear circuits
Content Type	Text
Resource Type	Article

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