|
論文 |
1. |
B. Widrow and M. A. Lehr, "30 years of adaptive neural networks: Perceptron, madaline, and backpropagation," Proc. IEEE, vol. 78, pp. 1415--1442, Sept. 1990.
[PDF]
|
2. |
Jian Hua Li, Anthony N. Michel, and Wolfgang Porod. Analysis and synthesis of a class neural networks: Linear systems operating on closed hypercube. IEEE Tarns. Circuits Syst., 36(11):1405-1422, November 1989.
[PDF]
|
3. |
R. P. Lippmann, "An introduction to computing with neural nets," IEEE Acoustics, Speech and Signal Processing Magazine, 2(4):4-22, April 1987.
[PDF]
|
4. |
S. Grossberg, E. Mingolla, and D. Todovoric, "A neural network architecture for preattentive vision," IEEE Trans. Biomed. Eng., 36:65--83, 1989.
[PDF]
|
5. |
Wang, D.; Arbib, M.A., "Complex temporal sequence learning based on short-term memory," Proc. IEEE, vol. 78, pp. 1536 --1543, Sept. 1990.
[PDF]
|
6. |
Amari, S.-i., "Mathematical foundations of neurocomputing," Proc. IEEE, vol. 78, pp. 1443 --1463, Sept. 1990.
[PDF]
|
7. |
Poggio, T. and Girosi, F., "Networks for approximation and learning," Proc. IEEE, vol. 78, pp. 1481 --1497, Sept. 1990.
[PDF]
|
8. |
Barnard, E., "Optimization for training neural nets," IEEE Trans. Neural Network, vol. 3, pp. 232 --240, Mar. 1992.
[PDF]
|
9. |
Kohonen, T., "The self-organizing map," Proc. IEEE, vol. 78, pp. 1464 --1480, Sept. 1990.
[PDF]
|
10. |
Hagan, M.T. and Menhaj, M.B., "Training feedforward networks with the Marquardt algorithm," IEEE Trans. Neural Network, vol. 5, pp. 989 --993, Nov. 1994.
[PDF]
|
11. |
Pei-Yih Ting and Iltis, R.A., "Diffusion network architectures for implementation of Gibbs samplers with applications to assignment problems," IEEE Trans. Neural Network, vol. 5, pp. 622 --638, July 1994
[PDF]
|
12. |
Iltis, R.A.; Ting, P.-Y., "Computing association probabilities using parallel Boltzmann machines," IEEE Trans. Neural Network, vol. 4, pp. 221 --233, Mar. 1993.
[PDF]
|
13. |
R. Battiti, "First and second order methods for learning:
Between steepest descent and Newton's method," Neural Computation, vol.
4, no. 2, pp. 141 --166, 1992. [PDF]
|
14. |
G. A. Carpenter and S. Grossberg, "A massively parallel architecture
for a self-organizing neural pattern recognition machine," Computer Vision,
Graphics, and Image Processing, vol. 37, pp. 54 --115, 1987. [PDF]
|
15. |
C. Charalambous, "Conjugate gradient algorithm for efficient
training of artificial neural networks," IEEE Proceeding, vol. 139, no.
3, pp. 301 --310, 1992. [PDF]
|
16. |
M. A. Cohen and S. Grossberg, "Absolute stability of global
pattern formation and parallel memory storage by competitive neural networks,"
IEEE Trans. on Systems, Man, and Cybernetics, vol. 13, no. 5, pp. 815
--826, 1983. [PDF]
|
17. |
J. L. Elman, "Finding structure in time," Cognitive Science,
vol. 14, pp. 179 --211, 1990. [PDF] |
18. |
K. Fukushima, S. Miyake and T. Ito, "Neocognitron: A neural
network model for a mechanism of visual pattern recognition," IEEE Trans.
on Systems, Man, and Cybernetics, vol. 13, no. 5., pp. 826 --834, 1983.
[PDF] |
19. |
K. Fukushima, "Neocognitron: A hierarchical neural network
capable of visual pattern recognition," Neural Networks, vol. 1, pp. 119
--130, 1988. [PDF] |
20. |
S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions,
and the Bayesian restoration of images," IEEE Trans. on Pattern Analysis
and Machine Intelligence, vol. 6, pp. 721 --741, 1984. [PDF] |
21. |
S. Grossberg, "How does the brain build a cognitive code?,"
Psychological Review, vol. 87, pp. 1--51, 1980. [PDF]
|
22. |
M. Heywood and P. Noakes, "A framework for improved training
of sigma-pi networks," IEEE Transactions of Neural Networks, vol. 6, no.
4, pp. 893 --903, 1995. [PDF] |
23. |
J. J. Hopfield, "Neural networks and physical systems with
emergent collective computational properties," Proceedings of the National
Academy of Sciences, vol. 79, pp. 2554 -2558, 1982. [PDF]
|
24. |
J. J. Hopfield, "Neurons with graded response have collective
computational properties like those of two-state neurons," Proceedings
of the National Academy of Sciences, vol. 81, pp. 3088 --3092, 1984. [PDF]
|
25. |
J. J. Hopfield and D. W. Tank, "'Neural' computation of decisions
in optimization problems," Biological Cybernetics, vol. 52, pp. 141 --152,
1985. [PDF]
|
26. |
K. M. Hornik, M. Stinchcombe and H. White, "Multilayer feedforward
networks are universal approximators," Neural Networks, vol. 2, no. 5,
pp. 359 --366, 1989. [PDF]
|
27. |
R. A. Jacobs, "Increased rates of convergence through learning
rate adaptation," Neural Networks, vol. 1, no. 4, pp. 295 --308, 1988.
[PDF]
|
28. |
R. A. Jacobs, M. I. Jordan, S. J. Nowlan and G. E. Hinton,
"Adaptive mixtures of local experts," Neural Computation, vol. 3, pp.
79--87, 1991. [PDF] |
29. |
T. Kohonen, "Correlation matrix memories," IEEE Transactions
on Computers, vol. 21, pp. 353 --359, 1972. [PDF]
|
30. |
B. Kosko, "Bidirectional associative memories," IEEE Transactions
on Systems, Man, and Cybernetics, vol. 18, no. 1, pp. 49--60, 1988. [PDF]
|
31. |
D. J. C. MacKay, "A practical bayesian framework for backproagation
networks," Neural Computation, vol. 4, pp. 448 --472, 1992. [PDF] |
32. |
A. N. Michel and J. A. Farrell, "Associative memories via
artificial neural networks," IEEE Control Systems Magazine, April, pp.
6-17, 1990. [PDF] |
33. |
A. K. Rigler, J. M. Irvine and T. P. Vogl, "Rescaling of
variables in backpropagation learning," Neural Networks, vol. 4, no. 2,
pp. 225 --229, 1991. [PDF]
|
34. |
D. E. Rumelhart, G. E. Hinton and R. J. Williams, "Learning
representations by back-propagating errors," Nature, vol. 323, pp. 533
--536, 1986. [PDF]
|
35. |
D. F. Specht, "Probabilistic neural networks," Neural Networks,
vol. 3, no. 1, pp. 109 -- 118, 1990. [PDF] |
36. |
D. F. Specht, "A General regression neural network," IEEE
Transactions on Neural Networks, vol. 2, no. 6, pp. 568 --576, 1991. [PDF]
|
37. |
D. W. Tank and J. J. Hopfield, "Simple 'neural' optimization
networks: An A/D converter, signal decision circuit and a linear programming
circuit," IEEE Transactions on Circuits and Systems, vol. 33, no. 5, pp.
533 --541, 1986. [PDF]
|
38. |
T. P. Vogl, J. K. Mangis, A. K. Zigler, W. T. Zink and D.
L. Alkon, "Accelerating the convergence of the backpropagation method,"
Biological Cybernetics, vol. 59, pp. 256 --264, Sept. 1988. [PDF]
|
39. |
P. J. Werbos, "Backpropagation through time: What it is
and how to do it," Proceedings of the IEEE, vol. 78, pp. 1550 -- 1560,
Oct. 1990.
[PDF] |
40. |
B. Widrow and R. Winter, "Neural nets for adaptive filtering and adaptive pattern recognition," IEEE Computer Magazine, pp. 25 --39, March 1988.
[PDF]
|
41. |
R. J. Williams and D. Zipser, "A learning algorithm for continually
running fully recurrent neural networks," Neural Computation, vol. 1,
pp. 270 --280, 1989. [PDF] |
42. |
A. Waibel, Tl Hanazawa, G. Hinton, K. Shikano and K. J. Lang,
"Phoneme recognition using time-delay neural networks," IEEE Transactions
on Acoustics, Speech and Signal Processing, vol. 37, pp. 328 -- 339, 1989.
[PDF] |
43. |
Linske, R., "Self-organization in a perceptual network,"
IEEE Computer Magazine, vol. 21, pp. 105 --117, March 1988. [PDF]
|
44. |
Carpenter, G.A. and Grossberg, S., "The ART of adaptive pattern recognition by a self-organizing neural network," IEEE Computer Magazine, vol. 21, pp. 77 --88, March 1988.
[PDF]
|
45. |
Fukushima, K., "A neural network for visual pattern recognition," IEEE Computer Magazine, vol. 21, pp. 65 --75, March 1988.
[PDF]
|
46. |
Kohonen, T., "The 'neural' phonetic typewriter," IEEE Computer Magazine, vol. 21, pp. 11 --22, March 1988.
[PDF]
|
47. |
[PDF]
|
48. |
[PDF]
|
49. |
[PDF]
|
50. |
[PDF]
|