%0 Journal Article
%T Optimal decision f usion given sens or rules<br>
%A Yunmin ZHU
%A Xiaorong LI
%A <br>
%J 控制理论与应用
%D 2005
%I 
%X When all the rules of sensor decision are known ,the optimal distributed decision fusion ,which relies only on the joint conditional probability densities , can be derived for very general decision systems. They include those systems with interdependent sensor observations and any network structure. It is also valid for m-ary Bayesian decision problems and binary problems under the Neyman- Pearson criterion. Local decision rules of a sensor with communication from other sensors that are optimal for the sensor itself are also presented ,which take the form of a generalized likelihood ratio test . Numerical examples are given to reveal some interesting phenomena that communication between sensors can improve performance of a senor decision ,but cannot guarantee to improve the global fusion performance when sensor rules were given before fusing.
%K Distributed decision
%K Optimal fusion
%K Likelihood ratio test
%K Sensor rule<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=7397CAEFDA71F917C663E8DE3B593513&yid=2DD7160C83D0ACED&vid=38B194292C032A66&iid=CA4FD0336C81A37A&sid=F4B561950EE1D31A&eid=318E4CC20AED4940&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0