Possibilistic fuzzy c-means clustering model using Kernel methods

Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet

Volumn 2, Issue , 2005, Pages 465-470

  Wu, Xiao Hong ^a,b   Zhou, Jian Jiang ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b JIANGSU UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; MATHEMATICAL MODELS; NUMERICAL METHODS;

EUCLIDEAN DISTANCE; KERNEL METHODS; KERNEL POSSIBILISTIC FUZZY C-MEANS MODEL (KPFCM); NONLINEAR PATTERNS;

FUZZY SETS;

EID: 33847214558     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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3. M. Barni, V. Cappellini and A. Mecocci, "Comments on A Possibilistic Approach to Clustering", IEEE Trans. Fuzzy Systems, vol. 4, No. 3, 1996, pp. 393-396.
4. N. R. Pal, K. Pal, and J. C. Bezdek, "A Possibilistic Fuzzy c-Means Clustering Algorithm", IEEE Trans. Fuzzy Systems, vol. 13, No. 4, 2005, pp. 517-530.
5. N. R. Pal, K. Pal, and J. C. Bezdek, "A New Hybrid c-Means Clustering Model", Proceedings of the IEEE International Conference On Fuzzy Systems, vol. 1, 2004, pp. 179-184.
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8. Z.-d. Wu, W.-x. Xie, "Fuzzy c-means clustering algorithm based on kernel method", The Fifth International Conference on Computational Intelligence and Multimedia Applications, 2003, pp. 1-6.
9. M. Aizerman, E. Braverman, and L. Rozonoer, "Theoretical foundations of the potential function method in pattern recognition learning", Automation and Remote Control, 25, 1964, pp. 821-837.