ENHANCEMENTS TO PROBABILISTIC NEURAL NETWORKS

Proceedings of the International Joint Conference on Neural Networks

Volumn 1, Issue , 1992, Pages 761-768

  Specht, Donald F ^a  

^a LOCKHEED MARTIN SPACE SYSTEMS COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BARIUM COMPOUNDS; CLUSTER ANALYSIS;

BAYES-OPTIMAL; CLUSTER CENTERS; CLUSTERING TECHNIQUES; DATA DISTRIBUTION; LEARN+; NEURAL-NETWORKS; ONE-PASS; OPTIMAL DECISION BOUNDARY; PROBABILISTICS; TRAINING PATTERNS;

NEURAL NETWORKS;

EID: 85008484889     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.1992.287095     Document Type: Conference Paper

References (13)

1. D. F. Specht, "Probabilistic Neural Networks for Classification, Mapping, or Associative Memory," Proceedings, IEEE International Conference on Neural Networks. 1, 525-532, June 1988.
2. D. F. Specht, "Probabilistic Neural Networks," Neural Networks, Vol. 3, pp. 109-118, 1990.
3. D. F. Specht, "Generation of Polynomial Discriminant Functions for Pattern Recognition," IEEE Trans, on Elec. Computers. Vol. EC-16, 1967, pp. 308-319.
4. D. F. Specht and P. D. Shapiro, "Training Speed Comparison of Probabilistic Neural Networks with Back-Propagation Networks," Proceedings of the International Neural Network Conference. Vol. 1, pp. 440-443, Paris, France, July 1990.
5. D. F. Specht and P. D. Shapiro, "Generalization Accuracy of Probabilistic Neural Networks compared with Back-Propagation Networks," Proceedings of the International Joint Conference on Neural Networks, Vol. 1, pp. 887-892, Seattle, Washington, July 1991.
6. P. Burrascano, "Learning Vector Quantization for the Probabilistic Neural Network," IEEE Trans, on Neural Networks, vol 2, pp. 458-461 (July 1991).
7. H. G. C. Traven, "A Neural Network Approach to Statistical Pattern Classification by 'Semiparametric' Estimation of Probability Density Functions," IEEE Trans, on Neural Networks, vol 2, pp. 366-377 (May 1991).
8. Ming-Lei Tseng, Integrating Neural Networks with Influence Diagrams for Multiple Sensor Diagnostic Systems. Ph.D. Dissertation, University of California at Berkeley, August 1991.
9. C. L. Scofield and D. L. Reilly, "Into Silicon: Real Time Learning in a High Density RBF Neural Network," Proceedings of the International Joint Conference on Neural Networks. Vol. 1, pp. 551-556, Seattle, Washington, July 1991.
10. J. C. Bezdek and P. F. Castelaz, "Prototype Classification and Feature Selection with Fuzzy Sets," IEEE Trans. SMC, SMC-7, pp. 87-92, 1977.
11. D. L. Reilly et al., "A neural model for category learning," Biol. Cybern., vol. 45, pp 35-41, 1982.
12. P. S. Maloney et al., "Successful applications of expanded probabilistic neural networks," in Intelligent Engineering Systems Through Artificial Neural Networks, Eds. C. H. Dagli et al., ASME PRESS, New York, 1991.
13. Roy Streit, personal communication at Naval Underwater Systems Center, Newport, R.I., Aug. 7-11, 1990.