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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jun Geng Lifeng Lai Bayraktar, E. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA (Jun Geng; Lifeng Lai) || Department of Mathematics, University of Michigan, Ann Arbor, MI (Bayraktar, E.) |
| Abstract | In this paper, quickest detection problem with sample right constraints is considered. Specifically, there is a sequence of samples whose probability density function will change at an unknown time. The goal is to detect such a change in a way that a linear combination of the detection delay and false alarm probability is minimized. However, one can take at most N observations from this random sequence. In this paper, we show that the cost function can be written as a set of iterative functions, which can be solved by optimal Markov stopping theorem. The optimal stopping rule is shown to be a threshold rule. To assist the analysis of the optimal scheme, several schemes whose delay performances bound the delay performance of the optimal scheme are developed. Asymptotic performance analysis indicates that the performance of the quickest detection with sample right constraints is close to that of the classic Bayesian quickest detection for several scenarios of practical interest. |
| Starting Page | 874 |
| Ending Page | 881 |
| File Size | 413501 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467345378 |
| e-ISBN | 9781467345392 |
| DOI | 10.1109/Allerton.2012.6483310 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-01 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | sequential detection Upper bound Simulation Observers Cost function limited sampling rights Bayes methods Delays Signal to noise ratio Bayesian change-point detection |
| Content Type | Text |
| Resource Type | Article |
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