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2004

Probabilistic fault diagnosis in communication systems through incremental hypothesis updating

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Probabilistic fault diagnosis in communication systems through incremental hypothesis updating
This paper presents a probabilistic event-driven fault localization technique, which uses a probabilistic symptomfault map as a fault propagation model. The technique isolates the most probable set of faults through incremental updating of a symptom-explanation hypothesis. At any time, it provides a set of alternative hypotheses, each of which is a complete explanation of the set of symptoms observed thus far. The hypotheses are ranked according to a measure of their goodness. The technique allows multiple simultaneous independent faults to be identified and incorporates both negative and positive symptoms in the analysis. As shown in a simulation study, the technique offers close-to-optimal accuracy and is resilient both to noise in the symptom data and to inaccuracies of the probabilistic fault propagation model.
Malgorzata Steinder, Adarshpal S. Sethi
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where CN
Authors Malgorzata Steinder, Adarshpal S. Sethi
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