The dependence identification neural network construction algorithm

IEEE Transactions on Neural Networks

Volumn 7, Issue 1, 1996, Pages 3-15

  Moody, John O ^a,b   Antsaklis, Panos J ^a,b  

^a IEEE

^b University of Notre Dame   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BACKPROPAGATION; BOOLEAN FUNCTIONS; LEARNING SYSTEMS; LINEAR ALGEBRA; MATHEMATICAL TRANSFORMATIONS; OPTIMIZATION; PROBLEM SOLVING; SPECIFICATIONS;

DEPENDENCE IDENTIFICATION; LINEAR EQUATIONS; NETWORK ARCHITECTURE; TRAINING ALGORITHMS;

NEURAL NETWORKS;

EID: 0029754431     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.478388     Document Type: Article

References (23)

1. E. B. Baum, "On the capabilities of multilayer perceptrons," J. Complexity, vol. 4, pp. 193-215, 1988.
2. D. Chester, "Why two hidden layers are better than one," in Proc. Int. Joint Conf. Neural Networks, 1990, pp. 265-268.
3. G. Cybenko, "Continuous value neural networks with two hidden layers are sufficient," Math. Contr. Signals Syst., vol. 2, pp. 303-314, 1989.
4. H. C. Elman, "Iterative methods for large sparse nonsymmetric systems of linear equations," Ph.D. dissertation, Comput. Sci. Dep., Yale Univ., New Haven, CT, 1982.
5. L. Fausett, Fundamentals of Neural Networks - Architecture, Algorithms, and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1994.
6. M. Frean, "The upstart algorithm: A method for constructing and training feedforward neural networks," Neural Computa., vol. 2, pp. 198-209, 1990.
7. R. Hecht-Nielsen, "Counterpropagation networks," Appl. Optics, vol. 26, no. 23, pp. 4979-4984, 1987.
8. J. Hertz, A. Krogh, and R. G. Palmer, Introduction to the Theory of Neural Computation. Reading, MA: Addison-Wesley, 1991.
9. G. E. Hinton, "Learning distributed representations of concepts," in Proc. 8th Annu. Conf. Cognitive Sci. Soc., 1986.
10. K. M. Hornik, M. Stinchocombe, and H. White, "Multilayer feedforward networks are universal approximators," Neural Networks, vol. 2, pp. 359-366, 1989.
11. L. K. Jones, "Constructive approximations for neural networks by sigmoidal functions," Proc. IEEE, vol. 78, no. 10, pp. 1586-1589, 1990.
12. D. Kincaid and W. Cheney, Numerical Anal. Monterey, CA: Brooks/Cole, 1991.
13. A. H. Kramer and A. Sangiovanni-Vincentelli, "Efficient parallel learning algorithm for neural networks," in Advances in Neural Information Processing Systems I, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1988, pp. 40-48.
14. M. Marchand, M. Golea, and P. Ruján, "A convergence theorem for sequential learning in two-layer perceptrons," Europhysics Lett., vol. 11, pp. 487-492, 1990.
15. M. Mézard and J.-P. Nadal, "Learning in feedforward neural networks: The tiling algorithm," J. Physics, vol. A, no. 22, pp. 2191-2204, 1989.
16. J. O. Moody, "A new method for constructing and training multilayer neural, networks," Master's thesis, Dep. Electrical Engineering, Univ. Notre Dame, IN, 1993.
17. N. J. Nilsson, Learning Machines. New York: McGraw-Hill, 1965.
18. F. Rosenblatt, Principles of Neurodynamics. New York: Spartan, 1962.
19. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing: Explanations in the Microstructure of Cognition, vol. 1: Foundation, D. E. Rumelhart and J. L. McClelland, Eds. Cambridge, MA: MIT Press, 1986, pp. 318-362.
20. M. A. Sartori and P. J. Antsaklis, "Neural network training via quadratic optimization," in Proc. ISCAS, San Diego, CA, May 10-13, 1992, and Tech. Rep. 90-05-01, Dep. Electrical Comput. Eng., Univ. Notre Dame, revised Apr. 1991.
21. _, "A simple method to derive bounds on the size and to train multilayer neural networks," IEEE Trans. Neural Networks, vol. 2, no. 4, pp. 467-471, July 1991.
22. R. Scalettar and A. Zee, "Emergence of grandmother memory in feed forward networks: Learning with noise and forgetfulness," in Connectionist Models and their Implications: Readings from Cognitive Science, D. Waltz and J. A. Feldman, Eds. Norwood, MA: Ablex, 1988, pp. 309-332.
23. G. Tesauro and B. Janssens, "Scaling relations in backpropagation learning," Complex Syst., vol. 2, pp. 39-44, 1988.