Uncertain Information Clustering Based on DempsterShafer Theory and HCM
CAO KeJin1, ZHAO ZongGui2, JIANG Han1
1.Institute of Command and Automation, PLA University of Science and Technology, Nanjing 210007 2.Insititute of the 28th Research Institute, China Electronics Technology Group Corporation, Nanjing 210014
Abstract：When analyzing multisource information, it is necessary to cluster the information according to their sources. In this paper, a problem of clustering multisource information denoted by evidence is investigated, and an evidence clustering standard is given. In addition, an idea of transformation from the evidence interspaces to Euclidean interspaces is presented in this paper, then the HCM is used to cluster the multisource information. Based on the theory, a simple example of passive sensors ESM tracking aerial target is demonstrated.
曹可劲，赵宗贵，江汉. 基于证据理论和硬c均值法的不确定性信息聚类[J]. 模式识别与人工智能, 2006, 19(3): 393-399.
CAO KeJin, ZHAO ZongGui, JIANG Han. Uncertain Information Clustering Based on DempsterShafer Theory and HCM. , 2006, 19(3): 393-399.
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2006, Vol. 19 
