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- Title
Analog Fault Diagnosis Using Conic Optimization and Ellipsoidal Classifiers.
- Authors
El-Gamal, Mohamed; Hassan, Abdel-Karim; Ibrahim, Ahmad
- Abstract
This paper introduces a new fault diagnosis strategy for analog circuits based on conic optimization and ellipsoidal classifiers. Ellipsoidal classifiers are trained for efficient and accurate fault classification of the circuit under test (CUT). In the testing phase, the output of the ellipsoidal classifiers is used to isolate the actual CUT fault. The constructed classifiers exhibit high classification rate with competitive computational complexity even if the CUT has overlapping faults. Experimental results demonstrate the superior performance of the ellipsoidal classifiers in analog fault diagnosis.
- Subjects
ANALOG circuits; CONIC sections; ELECTRIC fault location; FAULT indicators (Electricity); MATHEMATICAL optimization
- Publication
Journal of Electronic Testing, 2014, Vol 30, Issue 4, p443
- ISSN
0923-8174
- Publication type
Article
- DOI
10.1007/s10836-014-5466-4