Letters: The Multilayer Perceptron as an Approximation to a Bayes Optimal Discriminant Function

IEEE Transactions on Neural Networks

Volumn 1, Issue 4, 1990, Pages 296-298

  Ruck, Dennis W ^a   Rogers, Steven K ^a   Kabrisky, Matthew ^a   Oxley, Mark E ^a   Suter, Bruce W ^a  

^a AIR FORCE INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY - APPLICATIONS;

PERCEPTRONS; PROBABILITY FUNCTIONS;

NEURAL NETWORKS;

EID: 0025670892     PISSN: 10459227     EISSN: 19410093     Source Type: Journal    
DOI: 10.1109/72.80266     Document Type: Article

References (10)

1. D. W. Ruck, S. K. Rogers, and M. Kabrisky, “Target recognition: Conventional and neural network approaches,” in Proc. IEEE/INNS Int. Joint Conf. Neural Networks, 1989, Abstract.
2. S. K. Rogers, D. W. Ruck, M. Kabrisky, and G. L. Tarr, “Artificial neural networks for automatic target recognition,” in Proc. SPIE Conf. Appl. Artif. Neural Networks, Bellingham, WA, 1990.
3. D. W. Ruck, S. K. Rogers, and M. Kabrisky, “Tactical target recognition: Conventional and neural network approaches,” in Proc. 5th Ann. Aerospace Appl. Artif. Intell. Conf., Oct. 1989.
4. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. New York: Wiley, 1973.
5. P. J. Werbos, “Beyond regression: New tools for prediction and analysis in the behavioral sciences,” Ph.D. dissertation, Harvard Univ., Cambridge, MA, 1974.
6. D. B. Parker, “Learning-logic,” Stanford Univ., Stanford, CA, Invention Rep. 581-64, Oct. 1982.
7. D. E. Rumelhart, J. L. McClelland, and the PDP Research Group, Parallel Distributed Processing, vol. 1: Foundations. Cambridge, MA: M.I.T. Press, 1986.
8. S. Ross, A First Course in Probability. New York: Macmillan, 1976.
9. G. Cybenko, “Approximations by superpositions of sigmoidal functions,” Math. Contr., Signals, Syst., 1989.
10. H. White, “Learning in artificial neural networks: A statistical perspective,” Neural Comput., vol. 1, pp. 425-464, 1989.