Поисковый запрос: (<.>S=МНОГОСЛОЙНЫЕ ПЕРЦЕПТРОНЫ<.>) |
Общее количество найденных документов : 32
Показаны документы с 1 по 20
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1.
| An accelerated learning algorithm for multilayer perceptron networks // IEEE Trans. Neural Networks, 1994. Vol. 5, N 3.-С.493-497
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2.
| Anderson Dennis W. Improving the back propagation algorithm using scaler multiplication // Trans. Ill. State Acad. Sci, 1994. Vol. 87, Suppl..-С.41
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3.
| Asoh Nonlinear data analysis and multilayer perceptrons // IJCNN Int. Joint Conf. Neural Networks, Washington, 1989. -New York (N. Y.), 1989, Vol. 2.-С.411-415
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4.
| Back Andrew D. A simplified gradient algorithm for II R synapse multilayer perceptrons // Neural Comput., 1993. Vol. 5, N 3.-С.456-462
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5.
| Belue Lisa M. Selecting optimal experiments for multiple output multilayer perceptrons // Neural Comput., 1997. Vol. 9, N 1.-С.161-183
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| Burel Image compression using topological maps and MLP // IEEE Int. Conf. Neural Networks, San Francisco, Calif., March 29 - Apr. 1, 1993. -Piscataway (N. J.), 1993, Vol. 2.-С.727-731
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7.
| Chen Optimal initialization for multi-layer perceptrons // IEEE Int.Conf. Syst., Man, and Cybern., Los Angeles, Calif., Nov. 4-7, 1990. -New York (N. Y.), 1990.-С.370-372
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8.
| Chiang Using multithreshold quadratic sigmoidal neurons to improve classification capability of multilayer perceptron // IEEE Trans. Neural Networks, 1994. Vol. 5, N 3.-С.516-519
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9.
| Choi Sensitivity analysis of multilayer perceptron with differentiable activation functions // IEEE Trans. Neural Networks, 1992. Vol. 3, N 1.-С.101-107
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| Di Martino M. An efficient algorithm for the binary classification of patterns using MLP-networks // IEEE Int. Conf. Neural Networks, San Francisco, Calif., March 28-Apr. 1, 1993. -Piscataway (N. J.), 1993, Vol. 2.-С.936-943
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11.
| Emmerson Martin D. Determining and improving the fault tolerance of multilayer perceptrons in a pattern-recognition application // IEEE Trans. Neural Networks, 1993. Vol. 4, N 5.-С.788-793
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12.
| Errington Phil A. Classification of chromosomes using a combination of neural networks // IEEE Int. Conf. Neural Networks, San Francisco, Calif., March 29 - Apr. 1. 1993. -Piscataway (N. J.), 1993, Vol. 3.-С.1236-1241
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| Fogel David B. Using evolutionary programming to create neural networks that are capable of playing tic-tac-toc // IEEE Int. Conf. Neural Networks, San Francisco, Calif., March 28-Apr. 1, 1993. -Piscataway (N. J.), 1993, Vol. 2.-С.875-880
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14.
| Initializing weights of a multilayer perceptron network by using the orthogonal least squares algorithm // Neural Comput., 1995. Vol. 7, N 5.-С.982-999
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15.
| Karras D.A. On applying multilayer perceptron learning properties to (pseudo) random number generation and evaluation // Neural, Parall. and Sci. Comput., 1998. Vol. 6, N 4.-С.513-521
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16.
| Kerlirzin P. Robustness in multilayer perceptrons // Neural Comput., 1993. Vol. 5, N 3.-С.473-482
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17.
| Lippmann Richard P. Neural-net classifiers useful for speech recognition // IEEE Ist Int. Conf. Neural Networks, San Diego, Calif, June 21-24, 1987. -San Diego (Calif.), 1988, Vol. 4.-С.417-425
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18.
| Liu C.S. A new training algorithm multilayer discrete perceptrons // Neural, Parall. and Sci. Comput., 1998. Vol. 6, N 2.-С.217-228
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19.
| Oh Effects of nonlinear transformations on correlation between weighted sums in multilayer perceptron // IEEE Trans. Neural Networks, 1994. Vol. 5, N 3.-С.508-510
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20.
| Okamoto Efficient presentations of learning samples to accelerate the convergence of learning in multilayer perceptron // Images 21st Century. -New York (N. Y.), 1989, Pt 6/6.-С.2040-2041
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