A New Upper Bound For Finding Defective Samples In Group Testing
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS(2020)
摘要
The aim of this paper is to show an upper bound for finding defective samples in a group testing framework. To this end, we exploit minimization of Hamming weights in coding theory and define probability of error for our decoding scheme. We derive a new upper bound on the probability of error. We show that both upper and lower bounds coincide with each other at an optimal density ratio of a group matrix. We conclude that as defective rate increases, a group matrix should be sparser to find defective samples with only a small number of tests.
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关键词
defective samples, group testing, probability of error, upper bound
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