Quickest Change Detection In Anonymous Heterogeneous Sensor Networks

The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center. The sensors are clustered into K groups, and different groups follow different data generating distributions. At some unknown time, an event oc...

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Vydáno v:Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 5925 - 5929
Hlavní autoři: Sun, Zhongchang, Zou, Shaofeng, Li, Qunwei
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2020
Témata:
Anonymous
Change detection algorithms
Computational efficiency
Conferences
heterogeneous
hypothesis testing
mixture CuSum
sequential change detection
Signal processing
Signal processing algorithms
Speech processing
Testing
ISSN:2379-190X
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Shrnutí:The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center. The sensors are clustered into K groups, and different groups follow different data generating distributions. At some unknown time, an event occurs in the network and changes the data generating distribution of the sensors. The goal is to detect the change as quickly as possible, subject to false alarm constraints. The anonymous setting is studied in this paper, where at each time step, the fusion center receives n unordered samples. The fusion center does not know which sensor each sample comes from, and thus does not know its exact distribution. In this paper, a simple optimality proof is derived for the Mixture Likelihood Ratio Test (MLRT), which was constructed and proved to be optimal for the non-sequential anonymous setting in [1]. For the QCD problem, a mixture CuSum algorithm is constructed in this paper, and is further shown to be optimal under Lorden's criterion [2].
ISSN:2379-190X
DOI:10.1109/ICASSP40776.2020.9054079