|
[1]Bellman, R., Kalaba, R., and Zadeh, L.A., Abstraction and patterern classification, J. Math. Anal. Appl. 2 (1966) 581-585. [2]Bazdek, J.C., Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981. [3]Dave, R.N., Generalized fuzzy -shells clustering and detection of circular and elliptical boundaries, Pattern Recognition 25 (1992) 713-721. [4]Ruspini, E.H., A new approach to clustering, Inform. and Control 15 (1969) 22-32. [5]Tamura, S., Higuchi, S. and Tanaka, K., Pattern classification based on fuzzy relation, IEEE Trans. Systems Man Cybernet. (1978) 61-66. [6]Trauwaert, E., Kaufman, L., and Rousseeuw, P., Fuzzy clustering algorithms based on the maximum likelihood principle, Fuzzy Sets and Systems 42 (1991) 213-227. [7]Yang, M.S., A survey of fuzzy clustering, Math. Comput. Modell- ing 18 (1993) 1-16 [8]Yang, M.S., and Ko, C.H., On cluster-wise fuzzy regression analysis, IEEE Trans. Systems Man Cybernet.- Part B 27 (1997) 1-13. [9]Yang, M.S., and Su, C.F., On parameter estimation for normal mixtures based on fuzzy clustering algorithms, Fuzzy Sets and Systems 68 (1994) 13-28 [10]Yang, M.S., and Shih H.M., Cluster analysis based on fuzzy relations, Fuzzy Sets and Systems 120 (2001) 197-212 [11]Zadeh, L.A., Fuzzy Sets, Information and Control 8, 338-353 [12]Zadeh, L.A., Similarity relations and fuzzy ordering, Inform. Sci. 3 (1971) 177-200 [13]Zimmermann, H.J., Fuzzy Set Theory and Its Applications, Kluwer Academic Publishers, 1991
|