Abstract
The problem of quickest detection of an anomalous process among M processes is considered. At each time, a subset of the processes can be observed, and the observations follow two different distributions, depending on whether the process is normal or abnormal. The objective is a sequential search strategy that minimizes the expected detection time subject to an error probability constraint. This problem can be considered as a special case of active hypothesis testing first considered by Chernoff in 1959, where a randomized test was proposed and shown to be asymptotically optimal. For the special case considered in this paper, we show that a simple deterministic test achieves asymptotic optimality and offers better performance in the finite regime.
Original language | English |
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DOIs | |
State | Published - 1 Jan 2014 |
Externally published | Yes |
Event | 2014 IEEE Information Theory and Applications Workshop, ITA 2014 - San Diego, CA, United States Duration: 9 Feb 2014 → 14 Feb 2014 |
Conference
Conference | 2014 IEEE Information Theory and Applications Workshop, ITA 2014 |
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Country/Territory | United States |
City | San Diego, CA |
Period | 9/02/14 → 14/02/14 |
Keywords
- Sequential detection
- dynamic search
- hypothesis testing
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems