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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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