Training reformulated radial basis function neural networks capable of identifying uncertainty in data classification

IEEE Transactions on Neural Networks

Volumn 17, Issue 5, 2006, Pages 1222-1233

  Karayiannis, Nicolaos B ^a,b   Xiong, Yaohua ^a,b  

^a IEEE   (United States)

^b UNIVERSITY OF HOUSTON   (United States)

Author keywords

Cosine radial basis function (RBF); Feed forward neural network (FFNN); Gradient descent learning; Quantum neural network (QNN); Radial basis function neural network (RBFNN); Uncertainty

Indexed keywords

COSINE RADIAL BASIS FUNCTION; GRADIENT DESCENT LEARNING; QUANTUM NEURAL NETWORKS (QNNS); UNCERTAINTY;

CLASSIFICATION (OF INFORMATION); COSINE TRANSFORMS; FEEDFORWARD NEURAL NETWORKS; LEARNING ALGORITHMS; UNCERTAINTY ANALYSIS;

RADIAL BASIS FUNCTION NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPUTER ANALYSIS; COMPUTER SIMULATION; METHODOLOGY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; COMPUTING METHODOLOGIES; DATA INTERPRETATION, STATISTICAL; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 33750095441     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2006.877538     Document Type: Article

References (26)

1. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford, U.K.: Oxford Univ. Press, 1995.
2. R. Caruana and A. Niculescu-Mizil, "Predicting good probabilities with supervised learning," in Proc. Amer. Meteorology Conf. (AMS 2005), San Diego, CA, 2005, vol. 1.6A.
3. I. Cha and S. A. Kassam, "Interference cancellation using radial basis function networks," Signal Process., vol. 47, no. 3, pp. 247-268, 1995.
4. S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis function networks," IEEE Trans. Neural Netw., vol. 2, no. 2, pp. 302-309, Mar. 1991.
5. J. Gonzalez, I. Rojas, J. Ortega, H. Pomares, F. J. Fernandez, and A. F. Diaz, "Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation," IEEE Trans. Neural Netw., vol. 14, no. 6, pp. 1478-1495, Nov. 2003.
6. D. Heinke and F. H. Hamker, "Comparing neural networks: A benchmark on growing neural gas, growing cell structures, and fuzzy ARTMAP," IEEE Trans. Neural Netw., vol. 9, no. 6, pp. 1279-1291, Nov. 1998.
7. G.-B. Huang, P. Saratchandran, and N. Sundararajan, "A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation," IEEE Trans. Neural Netw., vol. 16, no. 1, pp. 57-67, Jan. 2005.
8. J.-S. R. Jang and C.-T. Sun, "Functional equivalence between radial basis function networks and fuzzy inference systems," IEEE Trans. Neural Netw., vol. 4, no. 1, pp. 156-159, Jan. 1993.
9. N. B. Karayiannis, "Reformulated radial basis neural networks trained by gradient descent," IEEE Trans. Neural Netw., vol. 10, no. 3, pp. 657-671, May 1999.
10. N. B. Karayiannis, R. Kretzschmar, and H. Richner, "Pattern classification based on quantum neural networks: A case study," in Pattern Recognition: From Classical to Modern Approaches, S. K. Pal and A. Pal, Eds. Singapore: World Scientific, 2001, pp. 301-328.
11. N. B. Karayiannis and W. Mi, "Growing radial basis neural networks: Merging supervised and unsupervised learning with network growth techniques," IEEE Trans. Neural Netw:, vol. 8, no. 6, pp. 1492-1506, Nov. 1997.
12. N. B. Karayiannis, A. Mukherjee, J. R. Glover, J. D. Frost, Jr., R. A. Hrachovy, and E. M. Mizrahi, "An evaluation of quantum neural networks in the detection of epileptic seizures in the neonatal electroencephalogram," Soft Comput. J., vol. 10, no. 4, pp. 382-396, 2006.
13. N. B. Karayiannis and G. Purushothaman, "Fuzzy pattern classification using feed-forward neural networks with multilevel hidden units," in Proc. IEEE Int. Conf. Neural Networks, Orlando, FL, Jun. 28-Jul. 2 1994, pp. 1577-1582.
14. N. B. Karayiannis and M. M. Randolph-Gips, "On the construction and training of reformulated radial basis function neural networks," IEEE Trans. Neural Netw., vol. 14, no. 4, pp. 835-846, Jul. 2003.
15. N. B. Karayiannis, G. Tao, Y. Xiong, A. Sami, B. Varughese, J. D. Frost, Jr., M. S. Wise, and E. M. Mizrahi, "Computerized motion analysis of videotaped neonatal seizures of epileptic origin," Epilepsia, vol. 46, no. 6, pp. 901-917, 2005.
16. N. B. Karayiannis, Y. Xiong, J. D. Frost, Jr., M. S. Wise, and E. M. Mizrahi, "Quantifying motion in video recordings of neonatal seizures by robust motion trackers based on block motion models," IEEE Trans. Biomed. Eng., vol. 52, no. 6, pp. 1065-1077, Jun. 2005.
17. L. Kuncheva and K. Atanassov, "An intuitionistic fuzzy RBF network," in Proc. 4th Euro. Congr. Intelligent Techniques and Soft Computing, Aachen, Germany, Sep. 2-5, 1996, pp. 777-781.
18. E. M. Mizrahi, "Neonatal seizures," in Childhood Seizures: Pediatric and Adolescent Medicine, S. Shinnar, N. Amir, and D. Branski, Eds. Basel, Switzerland: Krager, 1995, vol. 6, pp. 18-31.
19. J. E. Moody and C. J. Darken, "Fast learning in networks of locally-tuned processing units," Neural Comput., vol. 1, no. 2, pp. 281-294, 1989.
20. S. K. Pal and S. Mitra, Neuro-Fuzzy Pattern Recognition. New York: Wiley, 1999.
21. G. Purushothaman and N. B. Karayiannis, "Quantum neural networks (QNNs): Inherently fuzzy feedforward neural networks," IEEE Trans. Neural Netw., vol. 8, no. 3, pp. 679-693, May 1997.
22. G. Purushothaman and N. B. Karayiannis, "Feed-forward neural architectures for membership estimation and fuzzy classification," Int. J. Smart Eng. Syst. Design, vol. 1, pp. 163-185, 1998.
23. G. Purushothaman and N. B. Karayiannis, "On the capacity of feed-forward neural networks for fuzzy classification," J. Appl. Functional Anal., vol. 1, no. 1, pp. 9-32, 2006.
24. Q. M. Zhu and S. A. Billings, "Fast orthogonal identification of non-linear stochastic models and radial basis function neural networks," Int. J. Control, vol. 64, no. 5, pp. 871-886, 1996.
25. J. Zhou, Q. Gan, A. Krzyzak, and C. Y. Suen, "Quantum neural network in recognition of handwritten numerals," in Advances in Handwriting Recognition, S.-W. Lee, Ed. Singapore: World Scientific, 1999, pp. 368-377.
26. J. Zhou, "Automatic detection of premature ventricular contraction using quantum neural networks," in Proc. 3rd IEEE Symp. Bioinformatics and Bioengineering, Bethesda, MD, Mar. 10-12, 2003, pp. 169-173.