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.

Liva G., Paolini E., Chiani M. (2021). Optimum detection of defective elements in non-adaptive group testing. 345 E 47TH ST, NEW YORK, NY 10017 USA : Institute of Electrical and Electronics Engineers Inc. [10.1109/CISS50987.2021.9400279].

Optimum detection of defective elements in non-adaptive group testing

Paolini E.;Chiani M.
2021

Abstract

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.
2021
2021 55th Annual Conference on Information Sciences and Systems, CISS 2021
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Liva G., Paolini E., Chiani M. (2021). Optimum detection of defective elements in non-adaptive group testing. 345 E 47TH ST, NEW YORK, NY 10017 USA : Institute of Electrical and Electronics Engineers Inc. [10.1109/CISS50987.2021.9400279].
Liva G.; Paolini E.; Chiani M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/844038
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