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66. Grossberg S. Some networks that can learn, remember and reproduce any number of complicated space-time patterns. // Journal of Mathematics and Mechanics. - 1969. - V. 19, № 1. - P. 53-91. 67. Moody J.; Darken C. Learning in networks of locally-tuned processing units. // Neural Comput. - 1989. - V. 1, № 2. - P. 281-294. 68. Bishop C. Neural Networks for Pattern Recognition. - Oxford University Press: Walton Street, Oxford OX2 6DP. - 1995. - 251 p. 69. Hartman E.; Keeler J.D.; Kowalski J.M. Layered neural networks with Gaussian hidden units as universal approximations. // Neural Comput. - 1990. - V. 2, № 2. - P. 210-215. 70. MacQueen J.B. Some Methods for classification and Analysis of Multivariate Observations. // Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, University of California Press: Berkeley. - 1967. - V. 1. - P. 281-297. 71. Likas A.; Vlassis N.; Verbeek J.J. The Global K-Means Clustering Algorithm. // Pattern Recognit. - 2003. - V. 36, № 2. - P. 451-461. 72. Golub G.H.; Kahan W. Calculating the singular values and pseudoinverse of a matrix. // J. SIAM Numer. Anal. Ser. B - 1965. - V. 2, № 3. - P. 205-224. 73. Specht D. Probabilistic Neural Networks. // Neural Networks. - 1990. - V. 3, № 1. - P. 109-118. 74. Specht D. A General Regression Neural Network. // IEEE Trans. Neural Networks. - 1991. - V. 2, № 6. - P. 568-576. 75. Nadaraya E.A. On Non-Parametric Estimates of Density Functions and Regression Curves. // Theory. Probability Its Appl. - 1965. - V. 10, № 1. - P. 186-190. 76. Watson G.S. Smooth regression analysis. // Sankhya, Ser. A. - 1964. - V. 26, № 4. - P. 359-372. 77. Parzen E. On estimation of a probability density function and mode. // Annals of Mathenatical Statistics. - 1962. - V. 33, № 3. - P. 1065-1076. 78. Carpenter G.; Grossberg S. Neural dynamics of category learning and recognition: Attention, memory consolidation and amnesia. // Brain Structure, Learning and Memory (AAAS Symposium Series), Davis J.; Newburgh R.; Wegman E., Eds. Westview Press. - 1987. - P. 233-290. 320
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- Page 365: СПИСОК ОБОЗНАЧЕНИЙ
66. Grossberg S. Some networks that can learn, remember and reproduce any<br />
number of complicated space-time patterns. // Journal of Mathematics and Mechanics.<br />
- 1969. - V. 19, № 1. - P. 53-91.<br />
67. Moody J.; Darken C. Learning in networks of locally-tuned processing units. //<br />
Neural Comput. - 1989. - V. 1, № 2. - P. 281-294.<br />
68. Bishop C. Neural Networks for Pattern Recognition. - Oxford University Press:<br />
Walton Street, Oxford OX2 6DP. - 1995. - 251 p.<br />
69. Hartman E.; Keeler J.D.; Kowalski J.M. Layered neural networks with Gaussian<br />
hidden units as universal approximations. // Neural Comput. - 1990. - V. 2, № 2.<br />
- P. 210-215.<br />
70. MacQueen J.B. Some Methods for classification and Analysis of Multivariate<br />
Observations. // Proceedings of 5-th Berkeley Symposium on Mathematical Statistics<br />
and Probability, University of California Press: Berkeley. - 1967. - V. 1. - P. 281-297.<br />
71. Likas A.; Vlassis N.; Verbeek J.J. The Global K-Means Clustering Algorithm.<br />
// Pattern Recognit. - 2003. - V. 36, № 2. - P. 451-461.<br />
72. Golub G.H.; Kahan W. Calculating the singular values and pseudoinverse of a<br />
matrix. // J. SIAM Numer. Anal. Ser. B - 1965. - V. 2, № 3. - P. 205-224.<br />
73. Specht D. Probabilistic Neural Networks. // Neural Networks. - 1990. - V. 3,<br />
№ 1. - P. 109-118.<br />
74. Specht D. A General Regression Neural Network. // IEEE Trans. Neural Networks.<br />
- 1991. - V. 2, № 6. - P. 568-576.<br />
75. Nadaraya E.A. On Non-Parametric Estimates of Density Functions and Regression<br />
Curves. // Theory. Probability Its Appl. - 1965. - V. 10, № 1. - P. 186-190.<br />
76. Watson G.S. Smooth regression analysis. // Sankhya, Ser. A. - 1964. - V. 26,<br />
№ 4. - P. 359-372.<br />
77. Parzen E. On estimation of a probability density function and mode. // Annals<br />
of Mathenatical Statistics. - 1962. - V. 33, № 3. - P. 1065-1076.<br />
78. Carpenter G.; Grossberg S. Neural dynamics of category learning and recognition:<br />
Attention, memory consolidation and amnesia. // Brain Structure, Learning and<br />
Memory (AAAS Symposium Series), Davis J.; Newburgh R.; Wegman E., Eds.<br />
Westview Press. - 1987. - P. 233-290.<br />
320