Abstract
A decentralized sequential detection problem is considered where a set of sensors making independent observations must decide which of the given two hypotheses is true. Decision errors are penalized through a common cost function, and each time step taken by the sensors as a team is assigned a positive cost. It is shown that optimal sensor decision functions can be found in the class ofgeneralized sequential probability ratio tests (GSPRTs) with monotonically convergent thresholds. A technique is presented for obtaining the optimal thresholds. The performance of the optimal policy is compared with that of a policy which uses SPRTs at each of the sensors.
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This research was supported in part by the Joint Services Electronics Program under Grant N00014-90-J-1270, through the University of Illinois.
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Veeravalli, V.V., Başar, T. & Vincent Poor, H. Decentralized sequential detection with sensors performing sequential tests. Math. Control Signal Systems 7, 292–305 (1994). https://doi.org/10.1007/BF01211521
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DOI: https://doi.org/10.1007/BF01211521