Multivariate statistical pattern recognition with nonreduced dimensionality
Kybernetika, Tome 22 (1986) no. 2, pp. 142-157 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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Classification : 62H30, 68T10
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     title = {Multivariate statistical pattern recognition with nonreduced dimensionality},
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Grim, Jiří. Multivariate statistical pattern recognition with nonreduced dimensionality. Kybernetika, Tome 22 (1986) no. 2, pp. 142-157. http://geodesic.mathdoc.fr/item/KYB_1986_22_2_a3/

[1] L. E. Baum T. Petrie G. Soules, N. Weiss: A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann. Math. Statist. 41 (1970), 164-171. | MR

[2] A. P. Dempster N. M. Laird, and D. B. Rubin: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc. B 39 (1977), 1 - 38. | MR

[3] J. Grim: An algorithm for maximizing a finite sum of positive functions and its application to cluster analysis. Problems Control Inform. Theory 10 (1981), 427-437. | MR | Zbl

[4] J. Grim: On numerical evaluation of maximum-likelihood estimates for finite mixtures of distributions. Kybernetika 18 (1982), 173-190. | MR | Zbl

[5] J. Grim: Application of finite mixtures to multivariate statistical pattern recognition. In: Proceedings of DIANA Conf. held in Liblice near Prague, September 27-October 1, 1982.

[6] J. Grim: Design and optimization of multilevel homogeneous structures for multivariate pattern recognition. In: Proc. Fourth Formator Symposium (J. Beneš, L. Bakule, eds.), Academia, Prague 1983, pp. 223-240. | MR | Zbl

[7] J. Grim: On structural approximating multivariate discrete probability distributions. Kybernetika 20 (1984), 1-17. | MR | Zbl

[8] S. Kullback: Information Theory and Statistics. Dover, New York 1968. | MR

[9] M. A. G. Mattoso Maia, M. C. Fairhurst: On the use of I-divergence for generating distribution approximations. IEEE Trans. Pattern Anal, and Mach. Intel. PAMI-5 (1983), 661-664. | Zbl

[10] R. A. Redner, H. F. Walker: Mixture densities, maximum likelihood and the EM algorithm. SIAM Review 26 (1984), 195-239. | MR | Zbl

[11] M. I. Shlezinger: Relation between learning and self-learning in pattern recognition. (in Russian). Kibernetika (Kiev) (1968), 2, 81-88.

[12] C. F. J. Wu: On the convergence properties of the EM algorithm. Ann. Statist. 11 (1983), 95-103. | MR | Zbl