Flexible Takagi-Sugeno fuzzy systems

Proceedings of the International Joint Conference on Neural Networks

Volumn 3, Issue , 2005, Pages 1764-1769

  Cpałka, Krzysztof ^a,b   Rutkowski, Leszek ^a,b,c  

^a CZESTOCHOWA UNIVERSITY OF TECHNOLOGY   (Poland)

^b WSHE University in d   (Poland)

^c IEEE   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

NEURO-FUZZY SYSTEMS; TAKAGI-SUGENO FUZZY SYSTME;

NEURAL NETWORKS; PARAMETER ESTIMATION;

FUZZY SETS;

EID: 33750144040     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2005.1556147     Document Type: Conference Paper

References (14)

1. M. Gorazłczany, Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms. Springer-Verlag 2002.
2. J. S. Jang, C. T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing. Prentice Hall, Englewood Cliffs, 1997.
3. E. P. Klement, R. Mesiar, E. Pap, Triangular Norms. Kluwer Academic Publishers, Netherlands 2000.
4. C. T. Lin. Neural Fuzzy Control Systems with Structure and Parameter Learning, World Scientific, Singapore, 1994.
5. J. M. Mendel, Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice Hall PTR, Upper Saddle River, NJ, 2001
6. S. Mitaim and B. Kosko. The Shape of Fuzzy Sets in Adaptive Function Approximation, IEEE Trans. on Fuzzy Systems, vol. 9, pp. 637-656, 2001.
7. D. Nauck, F. Klawon and R. Kruse. Foundations of Neuro-Fuzzy Systems. Chichester, U.K.: Wiley, 1997.
8. L. Rutkowski, Flexible Neuro-Fuzzy Systenms. Kluwer Academic Publishers, 2004.
9. L. Rutkowski and K. Cpałka. Neuro-fuzzy systems derived from quasi triangular norms, IEEE Trans. Fuzzy Systems, vol. 13, February 2005.
10. L. Rutkowski and K. Cpałka. Flexible neuro-fuzzy systems, IEEE Trans. Neural Networks, vol. 14, pp.554-574, May 2003.
11. M. Sugeno and T. Yasukawa. A fuzzy-logic based approach to qualitative modeling, IEEE Trans. on Fuzzy Systems, vol. 1, pp. 7-31, Februay 1993.
12. T. Takagi and M. Sugeno. Fuzzy identification of systems and its application to modeling and control, IEEE Trans. Syst., Man, Cybern., vol. 15, pp. 116-132, 1985.
13. UCI respository of machine learning databases, C. J. Mertz, P. M. Murphy. Available online: http://www.ics.uci.edu/pub/machine -learning-databases.
14. R. R. Yager, D. P. Filev, Essentials of Fuzzy Modeling and Control. John Wiley & Sons, 1994.