A multiclass neural network classifier with fuzzy teaching inputs

Fuzzy Sets and Systems

Volumn 91, Issue 1, 1997, Pages 15-35

  Chen, Kuo Hsiu ^a   Chen, Hong Ling ^a   Lee, Hahn Ming ^a  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Exemplars; Fuzzy neural network; Fuzzy teaching inputs; Multiclass classification; Prototypes

Indexed keywords

FUZZY SETS; LEARNING ALGORITHMS; NEURAL NETWORKS; VECTOR QUANTIZATION;

FUZZY EXEMPLARS; FUZZY PROTOTYPES; FUZZY TEACHING INPUTS; MULTICLASS CLASSIFICATION;

PATTERN RECOGNITION SYSTEMS;

EID: 0031259418     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(96)00145-5     Document Type: Article

References (39)

1. V.U. Abe and M.S. Lan, A neural-network-based fuzzy classifier, IEEE Trans. Systems Man Cybernet. 25 {1995) 353-361.
2. M.A. Abounasr and M.A. Sidahmed, Fast learning and efficient memory utilization with a prototype based neural classifier, Pattern Recognition 28 (1995) 581 594.
3. N.P. Archer and S. Wang, Fuzzy set representation of neural network classification boundaries, IEEE Trans. Systems Man Cybernet. 21 (1991) 735-742.
4. J.C. Bezdek, Fuzzy models and computational neural networks, Tutorial of IEEE Conj. on Neural Networks for Ocean Engineering {1991) 291 300.
5. J.C. Bezdek, C.C. Taso and N.R. Pal, Fuzzy Kohonen clustering networks, Proe. lnternat. Conj. on Fuzz, Systems (1992) 1035-1043.
6. C.L. Chang, Finding prototypes for nearest neighbor classifiers, IEEE Trans. Comput. C-23 (1974) 1179-1184.
7. K.H Chen, H.L. Chen and H.M. Lee, A multiclass neural net classifier with fuzzy teaching inputs, to appear in EUFIT '95 3rd European Congress on Intelligent Techniques and Soft Computing (1995) 387-391.
8. S. Cho, O.K. Ersoy and M. Lehto, An algorithm to compute the degree of match in fuzzy systems, Fuzzy Sets and Systems 49 (1992) 285-299.
9. E. Cox, Integrating fuzzy logic into neural nets. AI Expert 6 1992 143-147.
10. K. Demura, M. Kajiura and Y. Anzai, The SOLAR algorithm, ICNN '94 IEEE lnternat. Conj'. on Neural Networks 1 (1994) 125-130.
11. F. Dicesare. Z. Sahnoun and P.P. Bonissone, Linguistic summarization of fuzzy data, Inlbrm. Sci. 52 (1990) 141 152.
12. D. Dubois and H. Prade, Fuzzy real algebra: some results, Fuzzy Sets and Systems 2 (1979) 327- 348.
13. M.M. Gupta and J. Qi, On fuzzy neuron models, IJCNN '91 lnternat. Joint Conf on Neural Networks (1991) 431-436.
14. C.J. Harris, C.G. Moore and M. Brown, Intelligent Control Aspects of Fuzzy Logic and Neural Nets (World Scientific, Singapore, 1993).
15. Y. Hayashi, A neural expert system using fuzzy teaching input, Proc. lnternat. Cot!If on Fuzzy Systems (1992) 485-491.
16. H. Ishibuchi, R. Fujioka and H. Tanaka, An architeclure of neural networks for input vectors of fuzzy numbers, Proc. Internat. Conf. on Fuzzy Systems (1992) 1293-1300.
17. C.I. Kao and Y.H. Kuo, A neural network model based on fuzzy classification concept, IJCNN lnternat. Joint Con£ on Neural Networks, Vol. 2 1992 727-732.
18. NB. Karayiannis and P.I. Pai, A fuzzy algorithm for learning vectors quantization, 1994 IEEE lnternat. Conf. on SMC (1994) 126-131.
19. R. Keller, Expert System-Development & Approaches (Prentice-Hall, Englewood Cliffs, N J, 1987).
20. T. Kohonen, SelJ:Organization and Associative Memory (Springer, New York, 1989).
21. B. Kosko, Neural Networks and Fuzzy Systems A Dynamical Systems Approach to Machine Intelligent (Prentice-Hall, Englewood Cliffs, N J, 1992).
22. H.K. Kwan and Y. Cai, A fuzzy neural network and its application to pattern recognition, IEEE Trans. Fuzzy Systems 2 (1994) 185-193.
23. H.M. Lee and C.S. Lai, Supervised fuzzy ART: training of neural network for pattern classification via combining supervised and unsupervised learning, 1993 IEEE Internat. Con£ on Neural Networks, Vol. 1 (1993) 323-328.
24. H.M. Lee and W.T. Wang, A neural network architecture for classification of fuzzy inputs, Fuzzy Sets and Systems 63 (1994) 159-173.
25. R.P. Lippmann, Pattern classification using neural networks, IEEE Comm. Maoazine 40 (1989) 185-234.
26. J.L. McClelland and D.E. Rumelhart, Explorations in Parallel Distributed Processiny (MIT Press, Cambridge, MA, 1988).
27. S.C. Newton and S. Mitra, An adaptive fuzzy system for control and clustering of arbitrary data patterns, IEEE lnternat. Conf. on Fuzzy Systems (1992) 363 370.
28. S.K. Pal and S. Mitra, Multilayer perceptron, fuzzy sets, and classifier, IEEE Trans. Neural Networks 3 (1992) 683 697.
29. W. Pedrycz and H.C. Card, Linguistic interpretation of self-organizing maps, Proc. Internat. Conf. on Fuzzy Systems (1992) 371-378.
30. D.E. Rumelhart and J.L. McClelland, Parallel Distributed Processiny, Vol. 1 (MIT Press, Cambridge, MA, 1987).
31. S. Salzberg, A nearest hyperrectangle learning method, Mach. Learning 6 (1991) 251-276.
32. J.W. Shjvlik, R.J. Mooney and F.G. Towell, Symbolic and neural learning algorithm: An experimental comparison, Machine Learning 6 (1991) 111-145.
33. P.K. Simpson, Fuzzy min-max neural networks - part 1: Classification, IEEE Trans. Neural Networks 3 (1992) 776-786.
34. P.K. Simpson, Fuzzy rain-max neural networks part 2: Clustering, IEEE Trans. on Fuzzy Systems 1 (1993) 32-45.
35. UCI repository of machine learning database, ftp://ics.uci.edu/pub/machine-learning-database.
36. R.R. Yager and L.A. Zadeh, Eds., An Introduction to Fuzzy Logic Applications in Intelligent Systems (Kluwer, Boston, MA, 1993).
37. T. Yamakawa and M. Furukawa, A design algorithm of membership functions for a fuzzy neuron using examplebased learning, Proc. Internat. Conf. on Fuzzy Systems (1992) 75-82.
38. L.A. Zadeh, Fuzzy sets, Inform. and Control g (1965) 338-353.
39. H.-J. Zimmermann, Fuzzy Set Theory and Its Applications (Kluwer, Boston, 1991).