Granular analysis in clustering based on the theory of fuzzy tolerance quotient space

  • Authors:

  • Lunwen Wang;Lunwu Wang;Zuguo Wu

  • Affiliations:

  • National Lab of Information Control Technology for Communication System, Jiaxing, China and Electronic Engineering Institute, Hefei;Electronic Engineering Institute, Hefei;Electronic Engineering Institute, Hefei

  • Venue:
  • RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
  • Year:
  • 2010

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Abstract

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.