On finding a set of healthy individuals from a large population

Sharma, Abhay and Murthy, Chandra R (2013) On finding a set of healthy individuals from a large population. In: 2013 Information Theory and Applications Workshop (ITA), 10-15 Feb. 2013, San Diego, CA.

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Abstract

In this paper, we explore fundamental limits on the number of tests required to identify a given number of ``healthy'' items from a large population containing a small number of ``defective'' items, in a nonadaptive group testing framework. Specifically, we derive mutual information-based upper bounds on the number of tests required to identify the required number of healthy items. Our results show that an impressive reduction in the number of tests is achievable compared to the conventional approach of using classical group testing to first identify the defective items and then pick the required number of healthy items from the complement set. For example, to identify L healthy items out of a population of N items containing K defective items, when the tests are reliable, our results show that O(K(L - 1)/(N - K)) measurements are sufficient. In contrast, the conventional approach requires O(K log(N/K)) measurements. We derive our results in a general sparse signal setup, and hence, they are applicable to other sparse signal-based applications such as compressive sensing also.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright of this article belongs to IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	16 Aug 2013 08:04
Last Modified:	16 Aug 2013 08:04
URI:	http://eprints.iisc.ac.in/id/eprint/47004

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