Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing

被引:2
|
作者
Petersen, Hendrik Bernd [1 ]
Agarwal, Shankar [2 ]
Jung, Peter [1 ]
Bah, Bubacarr [2 ]
机构
[1] Tech Univ Berlin, Commun & Informat Theory Grp, Berlin, Germany
[2] African Inst Math Sci, Data Sci Res Grp, Cape Town, South Africa
来源
2021 55TH ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS) | 2021年
关键词
group testing; compressed sensing; viral detection; non-negative; regression; NNLAD; COMP; sparse; compressible; noise;
D O I
10.1109/CISS50987.2021.9400261
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The problem of detecting few viral infections in a possibly large group with as few as possible tests can be modeled as either a group testing (GT) or a compressed sensing (CS) problem. CS approaches also allow to recover the viral load, but the underlying noise models are not common in CS and not well understood. Therefore, we study hybrid approaches that combine methods from CS and GT on various noise models. We compare the performance of such approaches with classical decoders from CS and GT. Our results show that combined strategies can improve the error rates and provide viral load estimation.
引用
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页数:5
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