Title :
Decentralized Bayesian sequential detection under uniformly distributed observations
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
We consider a couple of decentralized Bayesian sequential detection problems: the information structure of one is static, and that of the other is dynamic. Explicit member-by-member optimal solutions are derived under the assumption that the observations are uniformly distributed conditioned on each hypothesis. The resulting sequential detection rules are the same as those of analogous optimal centralized detectors.
Keywords :
Bayes methods; fault diagnosis; optimisation; sequential estimation; signal detection; decentralized Bayesian sequential detection; dynamic information structure; member by member optimal solutions; optimal centralized detectors; sequential detection rules; static information structure; uniformly distributed observations; Bandwidth; Bayesian methods; Cost function; Decision making; Detectors; Dynamic programming; Equations; Information analysis; Large-scale systems; Surveillance;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1185134
