Maximum-entropy clustering algorithm and its global convergence analysis

Science in China, Series E: Technological Sciences

Volumn 44, Issue 1, 2001, Pages 89-101

  Zhang, Zhihua ^a   Zheng, Nanning ^a   Shi, Gang ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Clustering algorithm; Convergence; Entropy function; Maximum entropy principle; Optimization method

Indexed keywords

EID: 0035245486     PISSN: 10069321     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02916729     Document Type: Article

References (16)

1. Bezdek, J. C., Pattern Recognition with Fuzzy Objective Function Algorithm. New York: Plenum, 1981.
2. Krishnapuram, R., Keller, J., A possibilistic approach to clustering, IEEE Trans. on Fuzzy Systems, 1993, 1(2): 98.
3. Yair, E., Zeger, K., Gersho, A., Competitive learning and soft competition for vector quantizer design, IEEE Trans on Signal Processing, 1992, 40(2): 294.
4. Pal, N. R., Bezdek, J. C., Tsao, E. C. K., Generalized clustering networks and Kohonen's self-organizing scheme, IEEE Trans on Neural Networks, 1993, 4(4): 549.
5. Karayiannis, N. B., Bezdek, J. C., Pal, N. R. et al., Repair to GLVQ: a new family of competitive learning schemes, IEEE Trans on Neural Networks, 1996, 7(5): 1062.
6. Karayiannis, N. B., Pai, P. I., Fuzzy algorithms for learning vector quantization, IEEE Trans. on Neural Networks, 1996, 7(5): 1196.
7. Karayiannis, N . B., A methodology for constructing fuzzy algorithms for learning vector quantization, IEEE Trans. on Neural Networks, 1997, 8(3): 505.
8. Karayiannis, N. B., Bezdek, J. C., An integrated approach to fuzzy learning vector quantization and fuzzy C-Means clustering, IEEE Trans. on Fuzzy Systems, 1997, 5(4): 622.
9. Li Xing-si, An efficient approach to nonlinear minimax problems, Chinese Science Bulletin, 1992, 37(10): 802.
10. Li Xing-si, An efficient approach to a class of non-smooth optimization problems, Science in China, Series A, 1994, 37(3): 323.
11. Zangwill, W., Non-linear Programming: A Unified Approach, Englewood Cliffs: Prentice-Hall, 1969.
12. Fletcher, R., Practical Methods of Optimization, 2nd ed., New York: John Wiley & Sons, 1987.
13. Zhang Zhihua, Zheng Nanning, Wang Tianshu, Behavioral analysis and improving of generalized LVQ neural network, Acta Automatica Sinica, 1999, 25(5): 582.
14. Kirkpatrick, S., Gelatt, C. D., Vecchi, M. P., Optimization by simulated annealing, Science, 1983, 220(3): 671.
15. Ross, K., Deterministic annealing for clustering, compression, classification, regression, and related optimization problems, Proceedings of the IEEE, 1998, 86(11): 2210.
16. Bezdek, J. C., Pal, N. R., Two soft relatives of learning vector quantization, Neural Networks, 1995, 8(5): 729.