Two-stage clustering via neural networks

IEEE Transactions on Neural Networks

Volumn 14, Issue 3, 2003, Pages 606-615

  Wang, Jung Hua ^a   Rau, Jen Da ^a   Liu, Wen Jeng ^b  

^a NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

^b NAN KAI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Clustering; Gravitation; k means; Neural networks; Quantization

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; CONVERGENCE OF NUMERICAL METHODS; DATA STRUCTURES; ERROR ANALYSIS; ITERATIVE METHODS; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING; VECTORS;

COMPETITIVE NEURAL NETWORK; GRAVITATION NEURAL NETWORK;

NEURAL NETWORKS;

EID: 0037844878     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2003.811354     Document Type: Article

References (29)

1. F. Hoppner, F. Klawonn, R. Kruse, and T. Runkler, Fuzzy Cluster Analysis. New York: Wiley, 1999.
2. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum, 1981.
3. E. Gose, R. Johnsonbaugh, and S. Jost, Pattern Recognition and Image Analysis. Englewood Cliffs, NJ: Prentice-Hall, 1996.
4. T. Kohonen, Self-Organization and Associative Memory. New York: Springer-Verlag, 1984, vol. 8, Springer Series in Information Sciences.
5. H. Frigui and R. Krishnapuram, "A robust competitive clustering algorithm with applications in computer vision," IEEE Trans. Pattern Anal. Machine Intell., vol. 21, pp. 450-465, May 1999.
6. J. C. Bezdek and N. R. Pal, "Some new indexes of cluster validity," IEEE Trans. Syst., Man Cybern., vol. 28, pp. 301-315, June 1998.
7. S. H. Kwon, "Cluster validity index for fuzzy clustering," Inst. Elect. Eng. Electron. Lett., vol. 34, no. 22, pp. 2176-2177, Oct. 1998.
8. A. O. Boudraa, "Dynamic estimation of number of clusters in data sets," Inst. Elect. Eng. Electron. Lett., vol. 35, no. 19, pp. 1606-1608, Sep. 1999.
9. J. M. Jolion, P. Meer, and S. Bataouche, "Robust clustering with applications computer vision," IEEE Trans. Pattern Anal. Machine Intell., vol. 13, pp. 791-802, Aug. 1991.
10. X. Zhuang, T. Wang, and P. Zhang, "A highly robust estimator through partially likelihood function modeling and its application in computer vision," IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 19-34, Jan. 1992.
11. X. Zhung, Y. Huang, K. Palaniappan, and J. S. Lee, "Gaussian mixture modeling, decomposition and applications," IEEE Trans. Image Processing, vol. 5, pp. 1293-1302, Sept. 1996.
12. F. Critchley, "The Euclidean structure of a dendogram, the variance of a node and the question: 'How many clusters really are there?," in Classification and Related Methods of Data Analysis, H. H. Bock, Ed. Amsterdam, The Netherlands: Elsevier, 1988, pp. 75-84.
13. R. C. Dubes, "How many clusters are best? -An experiment," Pattern Recognition, vol. 20, no. 6, pp. 645-663, 1987.
14. Y. Linde, A. Buzo, and R. M. Gray, "An algorithm for vector quantizer design," IEEE Trans. Commun., vol. COM-28, pp. 84-95, Jan. 1980.
15. S. P. Lloyd, "Least Squares Quantization in PCM," Bell Lab. Tech. Rep., Murray Hill, NJ, 1957.
16. S. Haykin, Neural Networks, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 1998.
17. C. T. Zahn, "Graph-theoretical methods for detecting and describing Gestalt clusters," IEEE Trans. Comput., vol. C-20, pp. 68-86, Jan. 1971.
18. Z. Wu and R. Leahy, "An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation," IEEE Trans. Pattern Anal. Machine Intell., vol. 15, pp. 1101-1113, Nov. 1993.
19. S. A. Galanopoulos and S. C. Ahalt, "Codeword distribution for frequency sensitive competitive learning with one-dimensional input data," IEEE Trans. Neural Networks, vol. 7, pp. 752-756, May 1996.
20. D. I. Choi and S. H. Park, "Self-creating and organizing neural networks," IEEE Trans. Neural Networks, vol. 5, pp. 561-575, July 1994.
21. T. M. Martinetz, S. G. Berkovich, and K. J. Schulten, "Neural-gas' network for vector quantization and its application to time-series prediction," IEEE Trans. Neural Networks, vol. pp. 558-569, July 1993.
22. B. Fritzke, "Growing cell structures-A self-organizing network for unsupervised and supervised learning," Neural Networks, vol. 7, no. 9, pp. 1441-1460, 1994.
23. T. V. Ravi and K. C. Gowda, "Clustering of symbolic objects using gravitational approach," IEEE Trans. Syst., Man, Cybern., vol. 29, pp. 888-894, Dec. 1999.
24. W. E. Wright, "Gravitational clustering," Pattern Recognition, vol. 9, no. 3, pp. 151-166, 1977.
25. A. Papoulis, Probability, Random Variables, and Stochastic Processes, 3rd ed. New York: McGraw-Hill, 1991.
26. R. N. Dave and R. Krishnapuram, "Robust clustering methods: A unified view," IEEE Trans. Fuzzy Syst., vol. 5, pp. 270-293, 1997.
27. C. Fraley, and A. E. Raftery, "How many clusters? Which clustering method? Answers via model-based cluster analysis," Comput. J., vol. 41, no. 8, pp. 578-588, 1998.
28. D. Allard and C. Fraley, "Nonparametric maximum likelihood estimation of features in spatial point processes using Voronoi tessellation," J. Amer. Statist. Assoc., vol. 92, pp. 1485-1493, 1997.
29. S. D. Byers and A. E. Raftery, "Nearest neighbor clutter removal for estimating features in spatial point processes," J. Amer. Statist. Assoc., vol. 93, pp. 577-584, 1998.