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• W2102344280 abstract "We propose a multiple-fault diagnosis method with high diagnosability, resolution, first-hit and short run time. The method has no assumption on fault models, thus can diagnose arbitrary faults. To cope with the multiple-fault mask and reinforcement effect, two key techniques of construction and scoring of fault-tuple equivalence trees are introduced to choose and rank the final candidate locations. Experimental results show that, when the circuits have 2 arbitrary faults, the average diagnosability and resolution are 98% and 0.95, respectively, with the best case 100% and 1.00. Moreover, in average, even when 21 arbitrary faults exist, our method can still identify 93% of them with the resolution 0.78, increased by 41% and 39% in comparison with the latest work where the diagnosability and resolution are 66% and 0.56. Finally, 96% of our top-ranked candidate locations are actual fault locations." @default.
• W2102344280 created "2016-06-24" @default.
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• W2102344280 date "2010-03-08" @default.
• W2102344280 modified "2023-09-27" @default.
• W2102344280 title "Diagnosis of multiple arbitrary faults with mask and reinforcement effect" @default.
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• W2102344280 doi "https://doi.org/10.5555/1870926.1871140" @default.
• W2102344280 hasPublicationYear "2010" @default.
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