Constructing Fuzzy Model by Self-Organizing Counterpropagation Network

IEEE Transactions on Systems, Man, and Cybernetics

Volumn 25, Issue 6, 1995, Pages 963-970

  Nie, Junhong ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

CONNECTION WEIGHTS; FUZZY RELATIONAL EQUATIONS; KNOWLEDGE EXTRACTOR; LINGUISTIC IF THEN STATEMENTS; MULTIVARIABLE FUZZY MODEL; SELF ORGANIZING COUNTERPROPAGATION NETWORK;

ALGORITHMS; COMPUTER SIMULATION; CONTROL SYSTEMS; FUZZY SETS; KNOWLEDGE ACQUISITION; KNOWLEDGE BASED SYSTEMS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MULTIVARIABLE SYSTEMS; NONLINEAR PROGRAMMING; NUMERICAL ANALYSIS; ONLINE SYSTEMS;

NEURAL NETWORKS;

EID: 0029323249     PISSN: 00189472     EISSN: 21682909     Source Type: Journal    
DOI: 10.1109/21.384258     Document Type: Article

References (19)

1. J. E. Box and G. M. Jenkins, Time Series Analysis, Forecasting and Control. San Francisco: Holden Day, 1970.
2. R. Hecht-Nielsen, “Counterpropagation network,” Applied Optics, vol. 26, pp. 4979–4984, 1987.
3. B. Kosko, Neural Networks and Fuzzy Systems. Englewood Cliffs, NJ: Prentice-Hall, 1992.
4. E. H. Mamdani, “Application of fuzzy algorithms for control of simple dynamic plant,” Proc. IEE, vol. 121, pp. 1585–1588.
5. K. Narendra and K. Parthasarathy, “Identification and control of dynamical systems using neural networks,” IEEE Trans. Neural Networks, vol. 1, pp. 4–27, 1990.
6. K. Narendra and K. Parthasarathy, “Neural networks and dynamical systems,” Int. J. Approximate Reasoning, vol. 6, pp. 109–131, 1992.
7. J. Nie, “A class of new fuzzy control algorithms,” in Proc. IEEE Int. Conf. on Control and Applications, Israel, 1989.
8. J. Nie and D. A. Linkens, “Fast self-learning multivariable fuzzy controllers constructed from modified CPN networks,” Int. J. Control, to appear.
9. J. Nie and D. A. Linkens, Fuzzy-Neural Control: Principles, Algorithms and Applications, Prentice-Hall International (UK), to appear.
10. W. Pedrycz, “An identification algorithm in fuzzy relational systems,” Fuzzy Sets and Systems, vol. 4, pp. 153–167, 1984.
11. I. S. Shaw and J. J. Kruger, “New fuzzy learning model with recursive estimation for dynamic systems,” Fuzzy Sets and Systems, vol. 48, pp. 217–229, 1992.
12. M. Sugeno and K. Tanaka, “Successive identification of a fuzzy model and its application,” Fuzzy Sets and Systems, vol. 42, pp. 315–334, 1991.
13. M. Sugeno and T. Yasukawa, “A fuzzy logic-based approach to qualitative modeling,” IEEE Trans. Fuzzy Systems, vol. 1, pp. 7–31, 1993.
14. H. Takagi and A. Hayashi, “NN-driven fuzzy reasoning,” Int. J. Approximate Reasoning, vol. 5, pp. 191–212, 1991.
15. R. M. Tong, “The evaluation of fuzzy model derived from experimental data,” Fuzzy Sets and Systems, vol. 4, pp. 1–12, 1980.
16. C. W. Xu and Y. Z. Lu, “Fuzzy model identification and self-learning for dynamic systems,” IEEE Trans. Syst. Man Cyber., vol. 17, pp. 683–689, 1987.
17. L. A. Zadeh, “Outline of a new approach to the analysis of complex systems and decision processes,” IEEE Trans. Syst. Man Cyber., vol. 3, pp. 28–44, 1973.
18. T. Kohonen, Self-Organizing and Associate Memory. New York: Springer-Verlag, 1984.
19. S. Grossberg, Studies of Mind and Brain, Boston, MA: Reidel, 1982.