一种基于目标和不完整数据特征的融合识别方法

Jun-wu Li, Zhi-fu Yu
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引用次数: 3

摘要

针对不完全数据融合识别的问题,提出了一种基于目标特征的融合识别方法。该方法首先根据观测向量得到特征的期望值,然后结合模糊推理方法得到证据。然后通过对证据重要性的分析,得出期望证据。最后运用D-S证据理论对期望证据进行融合,得到识别结果。仿真结果表明,该方法既能解决数据融合不完全的问题,又能避免证据冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A method of fusion recognition based on the characteristic of target and incomplete data
According to the problem of incomplete data fusion recognition, a method based on target characteristics is proposed. The expected values of characteristics are gained firstly based on observation vector in this method, and they are combined with fuzzy reasoning method to get the evidence. Then the expectation evidence is obtained through the analysis of the importance of evidence. Finally the D-S evidence theory is used to fusion expect evidence aiming to get recognition result. The simulation results show that the method can not only solve the problem of incomplete data fusion and also can avoid conflict evidence.
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