-
2
-
-
0028272769
-
-
5, pp. 130-148, 1994.
-
W. Atmar, "Notes on the simulation of evolution," IEEE Trans. Neural Networks, vol. 5, pp. 130-148, 1994.
-
"Notes on the Simulation of Evolution," IEEE Trans. Neural Networks, Vol.
-
-
Atmar, W.1
-
3
-
-
33747744730
-
-
883-890.
-
A. D. Back and A. C. Tsoi, "A comparison of discrete-time operator models for nonlinear system identification," in Advances in Neural Information Processing Systems 7, G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995, pp. 883-890.
-
"A Comparison of Discrete-time Operator Models for Nonlinear System Identification," in Advances in Neural Information Processing Systems 7, G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995, Pp.
-
-
Back, A.D.1
Tsoi, A.C.2
-
4
-
-
33747650992
-
-
155-161.
-
U. Bodenhausen and A. Waibel, "The tempo 2 algorithm: Adjusting time-delays by supervised learning," in Advances in Neural Information Processing Systems 3. San Mateo, CA: Morgan Kaufmann, 1991, pp. 155-161.
-
"The Tempo 2 Algorithm: Adjusting Time-delays by Supervised Learning," in Advances in Neural Information Processing Systems 3. San Mateo, CA: Morgan Kaufmann, 1991, Pp.
-
-
Bodenhausen, U.1
Waibel, A.2
-
5
-
-
33747676808
-
-
519-526.
-
Y. Cauvin, "A back-propagation algorithm with optimal use of hidden units," in Advances in Neural Information Processing Systems I, D. Touretzky, Ed., 1989, pp. 519-526.
-
"A Back-propagation Algorithm with Optimal Use of Hidden Units," in Advances in Neural Information Processing Systems I, D. Touretzky, Ed., 1989, Pp.
-
-
Cauvin, Y.1
-
6
-
-
0025448276
-
-
51, no. 6, pp. 1191-1214, 1990.
-
S. Chen, S. A. Billings, and P. M. Grant, "Non-linear system identification using neural networks," Int. J. Contr., vol. 51, no. 6, pp. 1191-1214, 1990.
-
S. A. Billings, and P. M. Grant, "Non-linear System Identification Using Neural Networks," Int. J. Contr., Vol.
-
-
Chen, S.1
-
7
-
-
0024611875
-
-
37, pp. 254-264, Feb. 1989.
-
Y.-F. Cheng and D. M. Etter, "Analysis of an adaptive technique for modeling sparse systems," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 254-264, Feb. 1989.
-
"Analysis of an Adaptive Technique for Modeling Sparse Systems," IEEE Trans. Acoust., Speech, Signal Processing, Vol.
-
-
Cheng, Y.-F.1
Etter, D.M.2
-
8
-
-
0031237543
-
-
8, pp. 1065-1070, 1997.
-
D. S. Clouse, C. L. Giles, B. G. Home, and G. W. Cottrell, "Time-delay neural networks: Representation and induction of finite state machines," IEEE Trans. Neural Networks, vol. 8, pp. 1065-1070, 1997.
-
C. L. Giles, B. G. Home, and G. W. Cottrell, "Time-delay Neural Networks: Representation and Induction of Finite State Machines," IEEE Trans. Neural Networks, Vol.
-
-
Clouse, D.S.1
-
9
-
-
33747708068
-
-
301-308.
-
J. Connor, L. E. Atlas, and D. R. Martin, "Recurrent networks and NARMA modeling," in Advances in Neural Information Processing Systems 4, 3. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds., 1992, pp. 301-308.
-
L. E. Atlas, and D. R. Martin, "Recurrent Networks and NARMA Modeling," in Advances in Neural Information Processing Systems 4, 3. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds., 1992, Pp.
-
-
Connor, J.1
-
10
-
-
33747742372
-
-
2, pp. 396104.
-
Y. Le Cun, J. S. Denker, and S. A. Solla, "Handwritten digit recognition with a backpropagation network," Advances in Neural Information Processing Systems, 1990, vol. 2, pp. 396104.
-
J. S. Denker, and S. A. Solla, "Handwritten Digit Recognition with a Backpropagation Network," Advances in Neural Information Processing Systems, 1990, Vol.
-
-
Le Cun, Y.1
-
11
-
-
33747660980
-
-
2, pp. 598-605.
-
-, "Optimal brain damage," in Advances in Neural Information Processing Systems, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990, vol. 2, pp. 598-605.
-
"Optimal Brain Damage," in Advances in Neural Information Processing Systems, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990, Vol.
-
-
-
12
-
-
0024861871
-
-
2, no. 4, pp. 303-314, 1989.
-
G. Cybenko, "Approximation by superpositions of a sigmoidal function," Math. Contr., Signals, Syst., vol. 2, no. 4, pp. 303-314, 1989.
-
"Approximation by Superpositions of a Sigmoidal Function," Math. Contr., Signals, Syst., Vol.
-
-
Cybenko, G.1
-
13
-
-
33747671348
-
-
J. E. Dayhoff, D.-T. Lin, and P. A. Ligomenides, "A learning algorithm for adaptive time-delays in a temporal neural network," Syst. Res. Center, Univ. Maryland, College Park, Tech. Rep. SRC-TR-92-59, 1992.
-
D.-T. Lin, and P. A. Ligomenides, "A Learning Algorithm for Adaptive Time-delays in a Temporal Neural Network," Syst. Res. Center, Univ. Maryland, College Park, Tech. Rep. SRC-TR-92-59, 1992.
-
-
Dayhoff, J.E.1
-
14
-
-
0027553120
-
-
4, pp. 348-354, 1993.
-
S. P. Day and M. R. Davenport, "Continuous-time temporal backpropagation with adaptable time delays," IEEE Trans. Neural Networks, vol. 4, pp. 348-354, 1993.
-
"Continuous-time Temporal Backpropagation with Adaptable Time Delays," IEEE Trans. Neural Networks, Vol.
-
-
Day, S.P.1
Davenport, M.R.2
-
15
-
-
0019583611
-
-
582-587, 1981.
-
D. M. Etter and S. D. Stearns, "Adaptive estimation of time delays in sampled data systems," IEEE Trans. AcousL, Speech, Signal Processing, vol. ASSP-29, pp. 582-587, 1981.
-
"Adaptive Estimation of Time Delays in Sampled Data Systems," IEEE Trans. AcousL, Speech, Signal Processing, Vol. ASSP-29, Pp.
-
-
Etter, D.M.1
Stearns, S.D.2
-
16
-
-
0026221027
-
-
2, pp. 490-497, 1991.
-
D. B. Fogel, "An information criterion for optimal neural network selection," IEEE Trans. Neural Networks, vol. 2, pp. 490-497, 1991.
-
"An Information Criterion for Optimal Neural Network Selection," IEEE Trans. Neural Networks, Vol.
-
-
Fogel, D.B.1
-
19
-
-
0024866495
-
-
2, no. 3, pp. 183-192, 1989.
-
K. Funahashi, " On the approximate realization of continuous mappings by neural networks," Neural Networks, vol. 2, no. 3, pp. 183-192, 1989.
-
" on the Approximate Realization of Continuous Mappings by Neural Networks," Neural Networks, Vol.
-
-
Funahashi, K.1
-
20
-
-
33747652889
-
-
C. L. Giles, B. G. Home, and T. Lin, "Learning a class of large finite state machines with a recurrent neural network," Inst. Adv. Comput. Studies, Univ. Maryland, College Park, Tech. Rep. UMIACS-TR-94-94 and CS-TR-3328, 1994.
-
B. G. Home, and T. Lin, "Learning a Class of Large Finite State Machines with a Recurrent Neural Network," Inst. Adv. Comput. Studies, Univ. Maryland, College Park, Tech. Rep. UMIACS-TR-94-94 and CS-TR-3328, 1994.
-
-
Giles, C.L.1
-
21
-
-
0029560406
-
-
8, no. 9, pp. 1359-1365, 1995.
-
___, "Learning a class of large finite state machines with a recurrent neural network," Neural Networks, vol. 8, no. 9, pp. 1359-1365, 1995.
-
"Learning a Class of Large Finite State Machines with a Recurrent Neural Network," Neural Networks, Vol.
-
-
-
23
-
-
33747731437
-
-
34-43.
-
J. Principe, L. Giles, N. Morgan, and E. Wilson, Eds. Piscataway, NJ: IEEE, 1997, pp. 34-43.
-
L. Giles, N. Morgan, and E. Wilson, Eds. Piscataway, NJ: IEEE, 1997, Pp.
-
-
Principe, J.1
-
24
-
-
0028495332
-
-
5, pp. 848-851, 1994.
-
C. L. Giles and C. W. Omlin, "Pruning recurrent neural networks for improved generalization performance," IEEE Trans. Neural Networks, vol. 5, pp. 848-851, 1994.
-
"Pruning Recurrent Neural Networks for Improved Generalization Performance," IEEE Trans. Neural Networks, Vol.
-
-
Giles, C.L.1
Omlin, C.W.2
-
25
-
-
0024991997
-
-
63, pp. 169-176, 1990.
-
F. Girosi and T. Poggio, "Networks and the best approximation property," Biolog. Cybern., vol. 63, pp. 169-176, 1990.
-
"Networks and the Best Approximation Property," Biolog. Cybern., Vol.
-
-
Girosi, F.1
Poggio, T.2
-
26
-
-
33747669961
-
-
41, pp. 190-195, 1979.
-
E. J. Hannan and B. G. Quinn, "The determination of the order of an autoregression," J. Royal Stat. Soc. B., vol. 41, pp. 190-195, 1979.
-
"The Determination of the order of an Autoregression," J. Royal Stat. Soc. B., Vol.
-
-
Hannan, E.J.1
Quinn, B.G.2
-
27
-
-
33747717972
-
-
B. Hassibi and D. G. Stork, "Second order derivatives for network pruning: Optimal brain surgeon," in Advances in Neural Information Processing Systems 5, S. J. Hanson, J. D. Cowan, and C. L. Giles, Eds. San Mateo, CA: Morgan Kaufmann, 1993.
-
"Second order Derivatives for Network Pruning: Optimal Brain Surgeon," in Advances in Neural Information Processing Systems 5, S. J. Hanson, J. D. Cowan, and C. L. Giles, Eds. San Mateo, CA: Morgan Kaufmann, 1993.
-
-
Hassibi, B.1
Stork, D.G.2
-
29
-
-
33747706701
-
-
697-704.
-
G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995, pp. 697-704.
-
D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995, Pp.
-
-
Tesauro, G.1
-
30
-
-
0024880831
-
-
2, no. 5, pp. 359-366, 1989.
-
K. Hornik, M. Stinchcombe, and H. White, "Multilayer feedforward networks are universal approximators," Neural Networks, vol. 2, no. 5, pp. 359-366, 1989.
-
M. Stinchcombe, and H. White, "Multilayer Feedforward Networks Are Universal Approximators," Neural Networks, Vol.
-
-
Hornik, K.1
-
31
-
-
0024125987
-
-
1, pp. 641-648.
-
B. Irie and S. Miyaké, "Capabilities of three-layered perceptrons," in Proc. IEEE Int. Conf. Neural Networks, San Diego, CA, 1988, vol. 1, pp. 641-648.
-
"Capabilities of Three-layered Perceptrons," in Proc. IEEE Int. Conf. Neural Networks, San Diego, CA, 1988, Vol.
-
-
Irie, B.1
Miyaké, S.2
-
32
-
-
0025447562
-
-
1, pp. 239-242, 1990.
-
E. D. Karnin, "A simple procedure for pruning back-propagation trained neural networks," IEEE Trans. Neural Networks, vol. 1, pp. 239-242, 1990.
-
"A Simple Procedure for Pruning Back-propagation Trained Neural Networks," IEEE Trans. Neural Networks, Vol.
-
-
Karnin, E.D.1
-
33
-
-
33747739109
-
-
A. Krogh and J. A. Hertz, "A simple weight decay can improve generalization," in Advances in Neural Information Processing Systems 4, J. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds., 1992, pp. 950-957.
-
"A Simple Weight Decay Can Improve Generalization," in Advances in Neural Information Processing Systems 4, J. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds., 1992, Pp. 950-957.
-
-
Krogh, A.1
Hertz, J.A.2
-
34
-
-
0025254722
-
-
3, no. 1, pp. 2-4, 1990.
-
K. J. Lang, A. H. Waibel, and G. E. Hinton, "A time-delay neural network architecture for isolated word recognition," Neural Networks, vol. 3, no. 1, pp. 2-4, 1990.
-
A. H. Waibel, and G. E. Hinton, "A Time-delay Neural Network Architecture for Isolated Word Recognition," Neural Networks, Vol.
-
-
Lang, K.J.1
-
35
-
-
0003645482
-
-
A. Lapedes and R. Farber, "Nonlinear signal processing using neural networks: Prediction and signal modeling," Los Alamos Nat. Labs., Los Alamos, NM, Tech. Rep. LA-UR-87-2662, 1987.
-
"Nonlinear Signal Processing Using Neural Networks: Prediction and Signal Modeling," Los Alamos Nat. Labs., Los Alamos, NM, Tech. Rep. LA-UR-87-2662, 1987.
-
-
Lapedes, A.1
Farber, R.2
-
36
-
-
0022011031
-
-
41, no. 2, pp. 303-328, 1985.
-
I. J. Leontaritis and S. A. Billings, "Input-output parametric models for nonlinear systems: Part I: Deterministic nonlinear systems," Int. J. Contr., vol. 41, no. 2, pp. 303-328, 1985.
-
"Input-output Parametric Models for Nonlinear Systems: Part I: Deterministic Nonlinear Systems," Int. J. Contr., Vol.
-
-
Leontaritis, I.J.1
Billings, S.A.2
-
37
-
-
0029079025
-
-
8, no. 3, pp. 447-461, 1995.
-
D. T. Lin, J. E. Dayhoff, and P. A. Ligomenides, "Trajectory production with the adaptive time-delay neural network," Neural Networks, vol. 8, no. 3, pp. 447-461, 1995.
-
J. E. Dayhoff, and P. A. Ligomenides, "Trajectory Production with the Adaptive Time-delay Neural Network," Neural Networks, Vol.
-
-
Lin, D.T.1
-
38
-
-
33646241633
-
-
7, pp. 1329-1338, 1996.
-
T.-N. Lin, B. G. Hörne, P. Tino, and C. L. Giles, "Learning long-term dependencies in narx recurrent neural networks," IEEE Trans. Neural Networks, vol. 7, pp. 1329-1338, 1996.
-
B. G. Hörne, P. Tino, and C. L. Giles, "Learning Long-term Dependencies in Narx Recurrent Neural Networks," IEEE Trans. Neural Networks, Vol.
-
-
Lin, T.-N.1
-
39
-
-
33747688352
-
-
T.-N. Lin, B. G. Hörne, and C. L. Giles, "How memory orders effect the performance of narx networks," Inst. Adv. Comput. Studies, Univ. Maryland, College Park, Tech. Rep. UMIACS-TR-96-76 and CS-TR-3706, 1996.
-
B. G. Hörne, and C. L. Giles, "How Memory Orders Effect the Performance of Narx Networks," Inst. Adv. Comput. Studies, Univ. Maryland, College Park, Tech. Rep. UMIACS-TR-96-76 and CS-TR-3706, 1996.
-
-
Lin, T.-N.1
-
40
-
-
33747723983
-
-
T. Lin, B. G. Hörne, P. Tino, and C. L. Giles, "Learning long-term dependencies is not as difficult with narx recurrent neural networks," in Advances in Neural Information Processing Systems 8. Cambridge, MA: MIT Press, 1996.
-
B. G. Hörne, P. Tino, and C. L. Giles, "Learning Long-term Dependencies Is not as Difficult with Narx Recurrent Neural Networks," in Advances in Neural Information Processing Systems 8. Cambridge, MA: MIT Press, 1996.
-
-
Lin, T.1
-
42
-
-
0027544506
-
-
8, pp. 343-348, 1993.
-
G. A. N. Mbamalu and M. E. El-Hawary, "Load forecasting via suboptimal seasonal autoregressive models and iteratively reweighted least squares estimation," IEEE Trans. Power Syst., vol. 8, pp. 343-348, 1993.
-
"Load Forecasting via Suboptimal Seasonal Autoregressive Models and Iteratively Reweighted Least Squares Estimation," IEEE Trans. Power Syst., Vol.
-
-
Mbamalu, G.A.N.1
El-Hawary, M.E.2
-
44
-
-
33747709361
-
-
847-854.
-
J. E. Moody, "The effective number of parameters: An analysis of generalization and regularization in nonlinear learning systems," in Advances in Neural Information Processing Systems 4, J. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds. San Mateo, CA: Morgan Kaufmann, 1992, pp. 847-854.
-
"The Effective Number of Parameters: an Analysis of Generalization and Regularization in Nonlinear Learning Systems," in Advances in Neural Information Processing Systems 4, J. E. Moody, S. J. Hanson, and R. P. Lippmann, Eds. San Mateo, CA: Morgan Kaufmann, 1992, Pp.
-
-
Moody, J.E.1
-
45
-
-
0041121576
-
-
11, pp. 3-26, 1989.
-
M. C. Mozer and P. Smolensky, "Skeletonization: A technique for trimming the fat from a network via relevance assessment," Connection Sei., vol. 11, pp. 3-26, 1989.
-
"Skeletonization: a Technique for Trimming the Fat from a Network via Relevance Assessment," Connection Sei., Vol.
-
-
Mozer, M.C.1
Smolensky, P.2
-
46
-
-
0025399567
-
-
1, pp. 4-27, 1990.
-
K. S. Narendra and K. Parthasarathy, "Identification and control of dynamical systems using neural networks," IEEE Trans. Neural Networks, vol. 1, pp. 4-27, 1990.
-
"Identification and Control of Dynamical Systems Using Neural Networks," IEEE Trans. Neural Networks, Vol.
-
-
Narendra, K.S.1
Parthasarathy, K.2
-
47
-
-
0027655722
-
-
40, pp. 877-885, 1993.
-
G. Nave and A. Cohen, "Ecg compression using long-term prediction," IEEE Trans. Biomed. Eng., vol. 40, pp. 877-885, 1993.
-
"Ecg Compression Using Long-term Prediction," IEEE Trans. Biomed. Eng., Vol.
-
-
Nave, G.1
Cohen, A.2
-
49
-
-
33747678650
-
-
4, no. 4, pp. 473193, 1992.
-
S. J. Nowlan and G. E. Hinton, "Simplifying neural networks by soft weight-sharing," Neural Comput., vol. 4, no. 4, pp. 473193, 1992.
-
"Simplifying Neural Networks by Soft Weight-sharing," Neural Comput., Vol.
-
-
Nowlan, S.J.1
Hinton, G.E.2
-
51
-
-
35949021230
-
-
45, pp. 712-715, 1980.
-
N. Packard, J. Crutchfield, D. Farmer, and R. Shaw, "Geometry from a time series," Phys. Rev. Lett., vol. 45, pp. 712-715, 1980.
-
J. Crutchfield, D. Farmer, and R. Shaw, "Geometry from a Time Series," Phys. Rev. Lett., Vol.
-
-
Packard, N.1
-
52
-
-
33747649712
-
-
M. W. Pedersen and L. K. Hansen, "Recurrent networks: Second order properties and pruning," in Advances in Neural Information Processing Systems 7, G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995.
-
"Recurrent Networks: Second order Properties and Pruning," in Advances in Neural Information Processing Systems 7, G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995.
-
-
Pedersen, M.W.1
Hansen, L.K.2
-
53
-
-
0026626377
-
-
3, pp. 122-130, 1992.
-
S.-Z. Qin, H.-T. Su, and T. J. McAvoy, "Comparison of four neural net learning methods for dynamic system identification," IEEE Trans. Neural Networks, vol. 3, pp. 122-130, 1992.
-
H.-T. Su, and T. J. McAvoy, "Comparison of Four Neural Net Learning Methods for Dynamic System Identification," IEEE Trans. Neural Networks, Vol.
-
-
Qin, S.-Z.1
-
54
-
-
0027662338
-
-
4, pp. 740-747, 1993.
-
R. Reed, "Pruning algorithms-A survey," IEEE Trans. Neural Networks, vol. 4, pp. 740-747, 1993.
-
"Pruning Algorithms-A Survey," IEEE Trans. Neural Networks, Vol.
-
-
Reed, R.1
-
55
-
-
0021466584
-
-
629-636, 1984.
-
J. Rissanen, "Universal coding, information, prediction, and estimation," IEEE Trans. Inform. Theory, vol. IT-30, pp. 629-636, 1984.
-
"Universal Coding, Information, Prediction, and Estimation," IEEE Trans. Inform. Theory, Vol. IT-30, Pp.
-
-
Rissanen, J.1
-
56
-
-
33751278790
-
-
65, pp. 579-616, 1991.
-
T. Sauer, J. Yorke, and M. Casdagli, "Embedology," J. Statist. Phys., vol. 65, pp. 579-616, 1991.
-
J. Yorke, and M. Casdagli, "Embedology," J. Statist. Phys., Vol.
-
-
Sauer, T.1
-
57
-
-
0041086018
-
-
5, pp. 179-187.
-
R. Shibata, "Various model selection techniques in time series analysis," in Handbook of Statistics. Amsterdam, The Netherlands: Else vier, 1985, vol. 5, pp. 179-187.
-
"Various Model Selection Techniques in Time Series Analysis," in Handbook of Statistics. Amsterdam, the Netherlands: else Vier, 1985, Vol.
-
-
Shibata, R.1
-
58
-
-
0031124173
-
-
27, p. 208, Apr. 1997.
-
H. T. Siegelmann, B. G. Hörne, and C. L. Giles, "Computational capabilities of recurrent narx neural networks," IEEE Trans. Syst., Man Cybern., pt. B, vol. 27, p. 208, Apr. 1997.
-
B. G. Hörne, and C. L. Giles, "Computational Capabilities of Recurrent Narx Neural Networks," IEEE Trans. Syst., Man Cybern., Pt. B, Vol.
-
-
Siegelmann, H.T.1
-
59
-
-
0026373081
-
-
3, pp. 2314-2319.
-
H.-T. Su and T. J. McAvoy, "Identification of chemical processes using recurrent networks," in Proc. Amer. Contr. Conf., 1991, vol. 3, pp. 2314-2319.
-
"Identification of Chemical Processes Using Recurrent Networks," in Proc. Amer. Contr. Conf., 1991, Vol.
-
-
Su, H.-T.1
McAvoy, T.J.2
-
60
-
-
0026868901
-
-
31, pp. 1338-1352, 1992.
-
H.-T. Su, T. J. McAvoy, and P. Werbos, "Long-term predictions of chemical processes using recurrent neural networks: A parallel training approach," Ind. Eng. Chem. Res., vol. 31, pp. 1338-1352, 1992.
-
T. J. McAvoy, and P. Werbos, "Long-term Predictions of Chemical Processes Using Recurrent Neural Networks: a Parallel Training Approach," Ind. Eng. Chem. Res., Vol.
-
-
Su, H.-T.1
-
61
-
-
84943236576
-
-
46-51.
-
C. Svarer, L. K. Hansen, and J. Larsen, "On design and evaluation of tapped-delay neural architectures," in Proc. IEEE Int. Conf. Neural Networks, 1992, pp. 46-51.
-
L. K. Hansen, and J. Larsen, "On Design and Evaluation of Tapped-delay Neural Architectures," in Proc. IEEE Int. Conf. Neural Networks, 1992, Pp.
-
-
Svarer, C.1
-
64
-
-
0026895542
-
-
5, no. 4, pp. 565-576, 1992.
-
B. de Vries and J. Principe, "The gamma model-A new neural network for temporal processing," Neural Networks, vol. 5, no. 4, pp. 565-576, 1992.
-
"The Gamma Model-A New Neural Network for Temporal Processing," Neural Networks, Vol.
-
-
De Vries, B.1
Principe, J.2
-
65
-
-
0024634603
-
-
37, pp. 328-339, 1989.
-
A. Waibel, T. Hanazawa, G. Hinton, K. Shikano, and K. Lang, "Phoneme recognition using time-delay neural networks," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 328-339, 1989.
-
T. Hanazawa, G. Hinton, K. Shikano, and K. Lang, "Phoneme Recognition Using Time-delay Neural Networks," IEEE Trans. Acoust., Speech, Signal Processing, Vol.
-
-
Waibel, A.1
-
66
-
-
33747664246
-
-
1, no. 3, pp. 193-209, 1990.
-
A. S. Weigend, B. A. Huberman, and D. E. Rumelhart, "Prediction the future: A connectionist approach," Int. J. Neural Syst., vol. 1, no. 3, pp. 193-209, 1990.
-
B. A. Huberman, and D. E. Rumelhart, "Prediction the Future: a Connectionist Approach," Int. J. Neural Syst., Vol.
-
-
Weigend, A.S.1
-
68
-
-
33747656319
-
-
12.
-
A. S. Weigend, B. A. Huberman, and D. E. Rumelhart, "Predicting sunspots and exchange rates with connectionist networks," in Nonlinear Modeling and Forecasting, SFI Studies in the Sciences of Complexity, M. Casdagli and S. Eubank, Eds. Reading, MA: Addison-Wesley, 1991, vol. 12.
-
B. A. Huberman, and D. E. Rumelhart, "Predicting Sunspots and Exchange Rates with Connectionist Networks," in Nonlinear Modeling and Forecasting, SFI Studies in the Sciences of Complexity, M. Casdagli and S. Eubank, Eds. Reading, MA: Addison-Wesley, 1991, Vol.
-
-
Weigend, A.S.1
-
69
-
-
33747714491
-
-
875-882.
-
A. S. Weigend, D. E. Rumelhart, and B. A. Huberman, "Generalization by weight-elimination with application to forecasting," in Advances in Neural Information Processing Systems 3, R. P. Lippmann, J. E. Moody, and D. S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1991, pp. 875-882.
-
D. E. Rumelhart, and B. A. Huberman, "Generalization by Weight-elimination with Application to Forecasting," in Advances in Neural Information Processing Systems 3, R. P. Lippmann, J. E. Moody, and D. S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1991, Pp.
-
-
Weigend, A.S.1
-
70
-
-
33747648507
-
-
13, pp. 43386.
-
R. J. Williams and D. Zipser, "Gradient-based learning algorithms for recurrent networks and their computational complexity," in BackPropagation: Theory, Architectures and Applications, Y. Chauvin and D. E. Rumelhart, Eds. Hillsdale, NJ: Lawrence Erlbaum, 1995, ch. 13, pp. 43386.
-
"Gradient-based Learning Algorithms for Recurrent Networks and Their Computational Complexity," in BackPropagation: Theory, Architectures and Applications, Y. Chauvin and D. E. Rumelhart, Eds. Hillsdale, NJ: Lawrence Erlbaum, 1995, Ch.
-
-
Williams, R.J.1
Zipser, D.2
-
71
-
-
84981426365
-
-
12, no. 4, pp. 363-373, 1989.
-
G.-H. Yu and Y.-C. Lin, "A methodology for selecting subset autoregressive time series models," J. Time Series Anal., vol. 12, no. 4, pp. 363-373, 1989.
-
"A Methodology for Selecting Subset Autoregressive Time Series Models," J. Time Series Anal., Vol.
-
-
Yu, G.-H.1
Lin, Y.-C.2
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