Decentralized Bayesian sequential detection under uniformly distributed observations

被引：0

作者：

Lee, JW ^{[1
]}

机构：

[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA

来源：

PROCEEDINGS OF THE 41ST IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4 | 2002年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：4772 / 4777

页数：6

共 12 条

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