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information-fusion-algorithm

于 2011-03-22 发布 文件大小:1385KB
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说明:  本文利用模糊理论中的高斯隶属 度函数来获得模糊观测下具有概率特性的似然函数,并且由此似然函数得到每个传感器提供信息的可信度;再将各传感器的可 信度转化成基本概率赋值函数即mass 函数;最后利用证据理论对多传感器信息进行融合。对目标识别的仿真试验表明该方法获 得的结果比直接结果具有更高的精度和可靠性。(The method uses fuzzy theory in the Gaussian fuzzy membership function to obtain a probable characteristic under observation likelihood function,and the resulting likelihood function gets the credibility of the information provided by the sensors.Then the reliability of each sensor is changed to a mass function.Finally,multi-sensor information is combined by using evidence theory.Simulation of target recognition shows that the results obtained have higher accuracy and reliability.)

文件列表:

利用模糊推理的证据理论信息融合算法.pdf,1490979,2011-03-05

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