A Distributed Bayesian Fusion Algorithm Research


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In this paper, the signal detection problem when distributed sensors are used a global decision is desired is considered. Local decisions from the sensors are fed to the data fusion center which then yields a global decision based on a fusion rule. Based on The data fusion theories of Bayesian criterion used for a distributed parallel structure, fusion rules at the fusion center、 the decision rules of sensors and the results of the computer simulation for two identical sensors, two different sensors and three identical sensors are presented. The results of the computer simulation show that the performance of the fusion system, compared with the sensor, has been improved. For the case there are three identical sensors in the fusion system, Bayesian risk is reduced by 26.5%, compared with the sensor.



Advanced Materials Research (Volumes 181-182)

Edited by:

Qi Luo and Yuanzhi Wang






S. J. Xu et al., "A Distributed Bayesian Fusion Algorithm Research", Advanced Materials Research, Vols. 181-182, pp. 1006-1012, 2011

Online since:

January 2011




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