Fuzzy system and CMAC network with B-spline membership/basis functions are smooth approximators

Soft Computing

Volumn 7, Issue 8, 2003, Pages 566-573

  Wang, S ^a,b   Lu, H ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b JIANGNAN UNIVERSITY   (China)

Author keywords

CMAC; Fuzzy system; Smooth function; Universal approximation

Indexed keywords

APPROXIMATORS; B-SPLINE BASIS FUNCTION; CMAC; CMAC NETWORK; CMAC NEURAL NETWORK; SMOOTH FUNCTIONS; THEORETICAL FOUNDATIONS; UNIVERSAL APPROXIMATION;

FUNCTIONS; INTERPOLATION; NEURAL NETWORKS;

FUZZY SYSTEMS;

EID: 33745917563     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-002-0242-2     Document Type: Article

References (12)

1. Kreinovich V, Nguyen HT, Yam Y (2000) Fuzzy systems are universal approximators for a smooth function and its derivatives. J Intelligent Syst 15: 565-574
2. Castro JL (1995) Fuzzy logic controllers are universal approximators. IEEE Trans. Systems, Man, Cybernetics, 25: 629-635
3. Wang S (2000) Neural-fuzzy systems and their programming, Publishing House of Science and Technology at Shanghai
4. Wang S (1998) Neuro-fuzzy systems and their applications. Press of Beijing Aeronautical Univ., Beijing
5. Lane SH, Handelman DA, Gelfand JJ (1992) Theory and development of high-order CMAC neural networks. IEEE Control Syst. Magazine 12: 23-30
6. Wang LX (1996) A course of fuzzy systems and control. Prentice-Hall Press, New York
7. Landajo M, Rio MJ, Perez R (2001) A note on smooth approximation capabilities of fuzzy Systems. IEEE Trans. Fuzzy Syst 9:
8. Albus J (1995) A new approach to manipulator control: the cerebellar model articulation controller CMAC, Trans, ASMEJ Dynamical Systems Measurement and Control 97: 220-227
9. Chiang CT, Lin CS (1996) CMAC with general basis functions, J. Neural Networks 9: 1199-1211
10. Wang S (2001) Research on fuzzy CMAC and its learning convergence, J. Advanced Software Research
11. Xu H, Kwan CM (1993) Real-time adaptive on-line traffic incident detection, J. Fuzzy Sets and Syst 93: 173-183
12. Lin CT (1997) Fuzzy systems and fuzzy neural networks, Prentice-Hall Press