Multiple Network Fusion Using Fuzzy Logic

IEEE Transactions on Neural Networks

Volumn 6, Issue 2, 1995, Pages 497-501

  Kim, Jin H ^b  

^a ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^b Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ARCHITECTURE; COMPUTER NETWORKS; FUZZY SETS; MATHEMATICAL MODELS; OPTIMIZATION; PATTERN RECOGNITION; RELIABILITY;

MEAN SQUARED ERRORS; NEURONS; ONLINE HANDWRITING CHARACTERS; POSTERIOR CLASS PROBABILITIES;

FEEDFORWARD NEURAL NETWORKS;

EID: 0029264250     PISSN: 10459227     EISSN: 19410093     Source Type: Journal    
DOI: 10.1109/72.363487     Document Type: Article

References (15)

1. L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, pp. 993-1001, 1990.
2. C. Scofield, L. Kenton, and J. Chang, “Multiple neural net architectures for character recognition,” in Proc. Compcon, pp. 487-491, San Francisco, CA: IEEE Computer Society Press, 1991.
3. R. A. Jacobs, M. I. Jordan, S. J. Nowlan, and G. E. Hinton, “Adaptive mixtures of local Neural Computation, vol. 3, 79-87, 1991.
4. D. Wolpert, “Stacked generalization,” Neural Networks, vol. 5, pp. 241-259, 1992.
5. M. P. Perrone and L. N. Cooper, “When networks disagree: Ensemble methods for hybrid neural networks,” Neural Networks for Speech and R. J. Mammone, Ed., Chapman-Hill, London, 1993.
6. J. B. Hampshire II and A. Waibel, “Connectionist architectures for multi-speaker phoneme recognition,” Advances in Neural Information Processing Systems, vol. 2, pp. 203-210, 1990.
7. M. D. Richard and R. P. Lippmann, “Neural network classifiers estimate Bayesian a posteriori probabilities,” Neural Computation, vol. 3, pp. 461-483, 1991.
8. S. Shlien, “Multiple binary decision tree classifiers,” Pattern Recognition, vol. 23, pp. 757-763, 1990.
9. M. Sugeno, “Fuzzy measures and fuzzy integrals: a survey,” Fuzzy Automata and Decision Processes. Amsterdam: North Holland, 1977, pp. 89-102.
10. K. Leszeynski, P. Penczek, and W. Grochulskki, “Sugenos fuzzy measures and fuzzy clustering,” Fuzzy Sets and Systems, vol. 15, pp. 147-158, 1985.
11. H. Tahani and J. M. Keller, “Information fusion in computer vision using the fuzzy integral,” IEEE Trans. Syst., Man, Cyhern., vol. 20, pp. 733-741, 1990.
12. R. R. Yager, “Element selection from a fuzzy subset using the fuzzy integral,” IEEE Trans. Syst, Man, Cybern., vol. 23, pp. 467-477, 1993.
13. S.-B. Cho and J. H. Kim, “Combining multiple neural networks by fuzzy integral for robust classification,” IEEE Trans. Syst., Man, Cybern, vol. 25, no. 1, 1995.
14. C. C. Tappert, C. Y. Suen, and T. Wakahara, “The state of the art in on-line handwriting recognition,” IEEE Trans. Pattern Analysis Machine Intelligence, vol. 12, no. 8, 787-808, 1990.
15. H. A. C. Eaton and T. L. Olivier, “Learning coefficient dependence on training set size,” Neural Networks, vol. 5, pp. 238-288, 1992.