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http://dx.doi.org/10.6109/jkiice.2019.23.10.1195

A Probabilistic Detection Algorithm for Noiseless Group Testing  

Seong, Jin-Taek (Department of Convergence Software, Mokpo National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.23, no.10, 2019 , pp. 1195-1200 More about this Journal
Abstract
This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes.
Keywords
Detection Algorithm; Group Testing; Failure Probability; Maximum a Posterior;
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