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Optimum Detection of Defective Elements in Non-Adaptive Group Testing

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arxiv 2102.05508 v1 pith:RQDQNS74 submitted 2021-02-10 cs.IT math.IT

Optimum Detection of Defective Elements in Non-Adaptive Group Testing

Gianluigi Liva , Enrico Paolini , Marco Chiani This is my paper
classification cs.IT math.IT
keywords testingdefectivefalsegroupnon-adaptiveprobabilityaddressedapplied
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We explore the problem of deriving a posteriori probabilities of being defective for the members of a population in the non-adaptive group testing framework. Both noiseless and noisy testing models are addressed. The technique, which relies of a trellis representation of the test constraints, can be applied efficiently to moderate-size populations. The complexity of the approach is discussed and numerical results on the false positive probability vs. false negative probability trade-off are presented.

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