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A deterministic annealing approach to clustering. (English) Zbl 0800.68817


MSC:

68T10 Pattern recognition, speech recognition
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[1] Rose K, Gurewtiz E, Fox G. A deterministic annealing approach to clustering. Patt Recog Lett, 1990, 11: 589-594 · Zbl 0800.68817
[2] Yu J, Shi H, Huang H, et al. Counterexamples to convergence theorem of maximum-entropy clustering algorithm. Sci China Ser F-Inf Sci, 2003, 46: 321-326 · Zbl 1186.62092
[3] Zhang Z H, Zheng N, Shi G. Maximum-entropy clustering algorithm and its alobal convergence analysis. Sci China Ser E, 2001, 44: 89-101 · Zbl 1232.90357
[4] Karayiannis N B. MECA: Maximum entropy clustering algorithm. In: Proc IEEE Int Conf Fuzzy Syst, Orlando, FL, 1994. 630-635
[5] Li R P, Mukaidono M. A maximum entropy approach to fuzzy clustering. In: Proc of the 4th IEEE Intern Conf on Fuzzy Systems, Yokohama, Japan, 1995. 2227-2232
[6] Karayiannis N B. Fuzzy partition entropies and entropy constrained fuzzy clustering algorithms. J Intell Fuzzy Syst, 1997, 5: 103-111
[7] Miyamoto S, Mukaidono M. Fuzzy c-means as a regularization and maximum entropy approach. In: Proc of the 7th International Fuzzy Systems Association World Congress, Vol. II, June 25-30, Prague, Chech, 1997. 86-92
[8] http://www.sagemath.com
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