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Granular Analysis in Clustering Based on the Theory of Fuzzy Tolerance Quotient Space

机译：基于模糊容差商空间理论的聚类粒度分析

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摘要

Clustering is defining an equivalence relation between the samples in nature, and two samples are equivalent if they belong to one class. The rough and fine of the granularity reflect the similarity threshold in clustering. In this paper, the disadvantage of granular analysis in clustering based on the theory quotient space, which can't solve the problem when there are intersections between classes, is pointed out, and the theory of fuzzy tolerance quotient space is introduced, and granular analysis in clustering based on the theory of fuzzy tolerance quotient space is presented. The results of the experiment about clustering radio communication signals show the efficiency of the algorithm.
机译：聚类定义了自然界中样本之间的等价关系，如果两个样本属于一类，则它们是等效的。粒度的粗略和精细反映了聚类中的相似性阈值。本文指出了基于商数空间理论的聚类分析的缺点，即当类之间有交集时不能解决问题，并介绍了模糊容限商空间的理论，并进行了粒度分析。提出了基于模糊容差商空间理论的聚类算法。聚类无线电通信信号的实验结果表明了该算法的有效性。

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  • 来源
    《Rough sets and knowledge technology》|2010年|p.743-750|共8页
  • 会议地点 Beijing(CN);Beijing(CN)
  • 作者

    Lunwen Wang; Lunwu Wang; Zuguo Wu;

  • 作者单位

    National Lab of Information Control Technology for Communication System, Jiaxing 314033, China,309 Research Room of Electronic Engineering Institute, Hefei, 230037;

    309 Research Room of Electronic Engineering Institute, Hefei, 230037;

    309 Research Room of Electronic Engineering Institute, Hefei, 230037;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 程序设计、软件工程;
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