Presentation 2013-03-08
An Analysis on Non-Adaptive Group Testing based on Sparse Pooling Graphs
Tadashi WADAYAMA,
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Abstract(in English) In this paper, an information theoretic analysis on non-adaptive group testing schemes based on sparse pooling graphs is presented. The binary status of objects to be tested are modeled by i.i.d. Bernoulli random variables with probability p. An (l, n)-regular pooling graph is a bipartite graph with left node degree l and right node degree r, where n is the number of left nodes. Two scenarios are considered; one is the noiseless setting and another is the noisy setting. The main contributions of this paper are direct part theorems which give conditions for existence of an estimator achieving arbitrary small estimation error probability. The direct part theorems are proved by averaging an upper bound on estimation error probability of the typical set estimator over an (l,r,n)-regular pooling graph ensemble. The numerical results obtained here indicate sharp threshold behaviors in the asymptotic regime.
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Keyword(in English) group testing / sparse graph / threshold / typical set estimator
Paper # IT2012-103,ISEC2012-121,WBS2012-89
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Committee IT
Conference Date 2013/2/28(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Analysis on Non-Adaptive Group Testing based on Sparse Pooling Graphs
Sub Title (in English)
Keyword(1) group testing
Keyword(2) sparse graph
Keyword(3) threshold
Keyword(4) typical set estimator
1st Author's Name Tadashi WADAYAMA
1st Author's Affiliation Nagoya Institute of Technology()
Date 2013-03-08
Paper # IT2012-103,ISEC2012-121,WBS2012-89
Volume (vol) vol.112
Number (no) 460
Page pp.pp.-
#Pages 6
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