A granular computing view on function approximation

2006 IEEE International Conference on Granular Computing

Volumn , Issue , 2006, Pages 232-237

  Zeng, Xiao Jun ^a   Keane, John A ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Function approximation; Fuzzy systems; Granular computing; Interval analysis; Neural networks

Indexed keywords

DATA PROCESSING; FUNCTION EVALUATION; FUZZY SETS; LEARNING SYSTEMS; NEURAL NETWORKS; PROBLEM SOLVING;

FUNCTION APPROXIMATION; FUZZY SYSTEMS; GRANULAR COMPUTING; INTERVAL ANALYSIS;

APPROXIMATION THEORY;

EID: 33751099067     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. A. R. Barron, "Universal approximation bounds for superpositions of a sigmoidal function," IEEE Trans. Inform. Theory, vol. 39, pp. 930-945, May 1993.
2. C.-C Chuang, S. -F. Su, J. -T. Jeng, C.-C. Hsiao, "Robust support vector regression networks for function approximation with outliers," IEEE Trans. Neural Networks, Vol. 13, pp. 1322-1330, Nov. 2002.
3. B. Delyon, A. Juditsky, and A. Benveniste, "Accuracy analysis for wavelet approximations," IEEE Trans. Neural Networks, Vol. 6, pp. 332-348, Mar. 1995.
4. D. Rogers, "A review of sales forecasting models most commonly applied in retail site evaluation," Int. J. Retail and Distribution Management, Vol. 20, No. 4, 1992.
5. F. Scarselli and Tsoi A. Chung, "Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results," Neural Networks, Vol. 11, pp. 15-37, Jan. 1998.
6. G. A. Watson, Approximation Theory and Numerical Methods, New York:John Wiley and Sons, 1980.
7. L.-X. Wang, "Fuzzy systems are universal approximators," in Proc. of IEEE int. conf. on Fuzzy Systems, San Diego, CA, pp. 1163-1170, Mar. 1992.
8. H. Ying, "Sufficient conditions on general fuzzy systems as function approximations," Automatica, Vol. 30, pp. 521-525, Mar. 1994.
9. L. A. Zadeh, "Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic," Fuzzy Sets Syst., vol. 90, pp. 111-127, 1997.
10. X.-J. Zeng and M.G. Singh, "Approximation theory of fuzzy systems - SISO case," IEEE Trans. Fuzzy Systems, Vol. 2, pp. 162-176, May 1994.
11. X.-J. Zeng and M.G. Singh, "Approximation theory of fuzzy systems - MIMO case," IEEE Trans. Fuzzy Systems, Vol. 3, pp. 219-235, May 1995.
12. X.-J. Zeng and M.G. Singh, "Approximation accuracy analysis of fuzzy systems as function approximators," IEEE Trans. Fuzzy Systems, Vol. 4, pp. 44-63, Feb. 1996.
13. X.-J. Zeng and J. A. Keane, "Approximation capabilities of hierarchical fuzzy systems," IEEE Trans. Fuzzy Systems, Vol. 13, pp. 659- 672, Oct. 2005.
14. Y.-Q., Zhang, "Constructive granular systems with universal approximation and fast knowledge discovery," IEEE Trans. Fuzzy Systems, Vol. 13, pp. 48-57, Feb. 2005.