A fuzzy modeling approach to decision fusion under uncertainty

被引：22

作者：

Samarasooriya, VNS ^{[1
]}

Varshney, PK ^{[1
]}

机构：

[1] Syracuse Univ, Dept Elect Engn & Comp Sci, Syracuse, NY 13244 USA

来源：

FUZZY SETS AND SYSTEMS | 2000年 / 114卷 / 01期

关键词：

fuzzy sets; decision fusion; Bayes criterion; total distance criterion; multi-sensor systems;

D O I：

10.1016/S0165-0114(98)00126-2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A multi-sensor decision fusion scheme is presented in which the probabilities associated with the local sensor decisions are known to vary in a nonrandom fashion around their design values. The uncertainties associated with the local decisions are modeled by means of fuzzy sets. A Bayesian approach is used to design the optimum fusion rule for the case where the local sensor decisions are statistically independent across the sensors. In order to reach a crisp decision, the global Bayesian risk is defuzzified using a criterion for mapping fuzzy sets on to the real line. The performance of the optimum fusion rule obtained is illustrated by means of a numerical example. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：59 / 69

页数：11

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