Bayesian quickest detection with unknown post-change parameter
In this paper, Bayesian quickest change-point detection problem with incomplete post-change information is considered. In particular, the observer knows that the post-change distribution belongs to a parametric distribution family, but he does not know the true value of the post-change parameter. Tw...
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| Vydané v: | Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 4169 - 4173 |
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| Jazyk: | English |
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01.03.2016
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| ISSN: | 2379-190X |
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| Abstract | In this paper, Bayesian quickest change-point detection problem with incomplete post-change information is considered. In particular, the observer knows that the post-change distribution belongs to a parametric distribution family, but he does not know the true value of the post-change parameter. Two problem formulations are considered in this paper. In the first formulation, we assume no additional prior information about the post-change parameter. In this case, the observer aims to design a detection algorithm to minimize the average (over the change-point) detection delay for all possible post-change parameters simultaneously subject to a worst case false alarm constraint. In the second formulation, we assume that there is a prior distribution on the possible value of the unknown parameter. For this case, we propose another formulation that minimizes the average (over both the change-point and the post-change parameter) detection delay subject to an average false alarm constraint. We propose a noval algorithm, which is termed as M-Shiryaev procedure, and show that the proposed algorithm is first order asymptotically optimal for both formulations considered in this paper. |
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| AbstractList | In this paper, Bayesian quickest change-point detection problem with incomplete post-change information is considered. In particular, the observer knows that the post-change distribution belongs to a parametric distribution family, but he does not know the true value of the post-change parameter. Two problem formulations are considered in this paper. In the first formulation, we assume no additional prior information about the post-change parameter. In this case, the observer aims to design a detection algorithm to minimize the average (over the change-point) detection delay for all possible post-change parameters simultaneously subject to a worst case false alarm constraint. In the second formulation, we assume that there is a prior distribution on the possible value of the unknown parameter. For this case, we propose another formulation that minimizes the average (over both the change-point and the post-change parameter) detection delay subject to an average false alarm constraint. We propose a noval algorithm, which is termed as M-Shiryaev procedure, and show that the proposed algorithm is first order asymptotically optimal for both formulations considered in this paper. |
| Author | Lifeng Lai Jun Geng |
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| Snippet | In this paper, Bayesian quickest change-point detection problem with incomplete post-change information is considered. In particular, the observer knows that... |
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| SubjectTerms | Algorithm design and analysis Algorithms Asymptotic properties Atmospheric measurements Bayes methods Bayesian analysis Bayesian quickest change detection Change detection algorithms Conferences Delay Delays Detection algorithms False alarms Formulations M-Shiryaev procedure Observers Optimization sequential detection unknown postchange parameter |
| Title | Bayesian quickest detection with unknown post-change parameter |
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