Autor:	Liva, Gianluigi, Paolini, Enrico, Chiani, Marco
Rok vydání:	2021
Předmět:	Computer Science - Information Theory
Druh dokumentu:	Working Paper
Popis:	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. Comment: To be presented at the special session on Data Science for COVID-19 at CISS 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2102.05508 Zobrazit plný text záznamu View this record from Arxiv