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Li, Y. and Li, G. (2010) Fast Fuzzy c-Means Clustering Algorithm with Spatial Constraints for Image Segmentation, Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, 67, 431-438.
http://dx.doi.org/10.1007/978-3-642-12990-2_49

has been cited by the following article:

• TITLE: A Fixed Suppressed Rate Selection Method for Suppressed Fuzzy C-Means Clustering Algorithm

  AUTHORS: Jiulun Fan, Jing Li

  KEYWORDS: Hard C-Means Clustering Algorithm, Fuzzy C-Means Clustering Algorithm, Suppressed Fuzzy C-Means Clustering Algorithm, Suppressed Rate

  JOURNAL NAME: Applied Mathematics, Vol.5 No.8, May 8, 2014

  ABSTRACT: Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In the algorithm, how to select the suppressed rate is a key step. In this paper, we give a method to select the fixed suppressed rate by the structure of the data itself. The experimental results show that the proposed method is a suitable way to select the suppressed rate in suppressed fuzzy c-means clustering algorithm.