SOME PROPERTIES OF OPTIMAL THRESHOLDS IN DECENTRALIZED DETECTION

被引：28

作者：

IRVING, WW

TSITSIKLIS, JN

机构：

[1] Department of Electrical Engineering, Massachusetts Institute of Technology, Cambridge

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1994年 / 39卷 / 04期

关键词：

Decentralized detection problem - Decision rules - Gaussian noise binary hypothesis problem - Optimal thresholds;

D O I：

10.1109/9.286264

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A decentralized Bayesian hypothesis testing problem is considered. It is analytically demonstrated that for the known signal in the Gaussian noise binary hypothesis problem, when there are two sensors with statistically independent identically distributed Gaussian observations (conditioned on the true hypothesis), there is no loss in optimality in using the same decision rule at both sensors. Also, a multiple hypothesis problem is considered; some structure is analytically established for an optimal set of decision rules.

引用

页码：835 / 838

页数：4

共 6 条

[1]

Abromowitz M., 1964, HDB MATH FUNCTIONS

[2] DESIGN AND PERFORMANCE COMPARISON OF DISTRIBUTED DETECTION NETWORKS [J].