Self-constructing fuzzy neural networks with extended Kalman filter

International Journal of Fuzzy Systems

Volumn 12, Issue 1, 2010, Pages 66-72

  Er, M J ^a   Liu, F ^b   Li, M B ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NONE

Author keywords

Dynamic system identification; Extended Kalman filter; Function approximation; Fuzzy neural networks; Mackey Glass time series prediction

Indexed keywords

APPROXIMATION ALGORITHMS; BANDPASS FILTERS; FUZZY FILTERS; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; LEARNING ALGORITHMS; PARAMETER ESTIMATION; RELIGIOUS BUILDINGS; TIME SERIES;

COMPACT STRUCTURES; DYNAMIC SYSTEM IDENTIFICATION; FREE PARAMETERS; FUNCTIONS APPROXIMATIONS; FUZZY-NEURAL-NETWORKS; HIGH-ACCURACY; MACKEY-GLASS TIME SERIES PREDICTIONS; PERFORMANCE; SELF-CONSTRUCTING FUZZY NEURAL NETWORKS; SIMPLE++;

EXTENDED KALMAN FILTERS;

EID: 77950953459     PISSN: 15622479     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (30)

1. Y. Lu, N. Sundararajan, and P. Saratchandran, "A sequential learning scheme for function approximation using minimal radial basis function neural networks," Neural Computation, vol.9, no.2, pp. 461-478, 1997. (Pubitemid 127635401)
2. J. Deng, N. Sundararajan, and P. Saratchandran, "Communication channel equalization using complex - valued minimal radial basis function neural networks," IEEE Transactions on Neural Networks, vol.13, no.3, pp. 687-696, 2002. (Pubitemid 34669656)
3. S. Wu and M. J. Er, "Dynamic fuzzy neural networks - a novel approach to function approximation," IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol.30, no.2, pp. 358-364, 2000.
4. Y. Lu., N. Sundararajan, and P. Saratchandran, "Identification of time-varying nonlinear systems using minimal radial basis function neural networks," IEE Proceedings: Control Theory and Applications, vol.144, no.2, pp. 202-208, 1997.
5. K. S. Narendra and K. Parathasarathy, "Identification and control of dynamic systems using neural networks," IEEE Transactions on Neural Networks, vol.1, no.1, pp. 4-27, 1990.
6. A. U. Levin and K. S. Narendra, "Control of nonlinear dynamical system using neural networks- part II: Observability, identification, and control," IEEE Transactions on Neural Networks, vol.7, no.1, pp. 30-42, 1996. (Pubitemid 126811726)
7. L. X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis, Englewood Cliffs, NJ: Prentice-Hall, 1994.
8. J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Englewood Cliffs, NJ: Prentice-Hall, 1997.
9. K. B. Cho and B. H. Wang, "Radial basis function based adaptive fuzzy systems and their applications to system identification and prediction," Fuzzy Sets and Systems, vol.83, no.3, pp. 325-339, 1996.
10. J. S. R. Jang, "ANFIS: Adaptive-Network-Based Fuzzy Inference System," IEEE Transactions on Systems, Man, and Cybernetics, vol.23, no.3, pp. 665-684, 1993.
11. J. S. Wang and C. S. G. Lee, "Efficient neuro-fuzzy control systems for autonomous underwater vehicle control," Proceedings of IEEE International Conference on Robotics and Automation 3, pp. 2986-2991, 2001. (Pubitemid 32815657)
12. C. T. Lin and C. S. G. Lee, Neural Fuzzy Systems: A Neural-Fuzzy Synergism to Intelligent Systems, Englewood Cliffs, NJ: Prentice-Hall, May 1996.
13. K. Tanaka, M. Sano, and H. Watanabe, "Modeling and control of carbon monoxide concentration using a neuro-fuzzy technique," IEEE Transactions on Fuzzy Systems, vol.3, no.3, pp. 271-279, 1995.
14. F. Y. Wang and H. M. Kim, "Implementing adaptive fuzzy logic controllers with neural networks: A design paradigm," Journal of Intelligent and Fuzzy Systems, vol.3, no.2, pp. 605-614, 1995.
15. D. A. Linkens and H. O. Nyongesa, "Learning systems in intelligent control: An appraisal of fuzzy, neural and genetic algorithm control applications," IEE Proceeding: Control Theory and Applications, vol.143, no.4, pp. 367-386, 1996.
16. C. F. Juang and C. T. Lin, "An on-line self-constructing neural fuzzy inference network and its applications," IEEE Transactions on Fuzzy Systems, vol.6, no.1, pp. 12-32, 1998. (Pubitemid 128747936)
17. J. Platt, "A resource-allocating network for function interpolation," Neural Computation, vol.3, no.2, pp. 213-225, 1991.
18. V. Kadirkamanathan and M. Niranjan, "A function estimation approach to sequential learning with neural networks," Neural Computation, vol.5, no.6, pp. 954-975, 1993.
19. Y. Lu, N. Sundararajan, and P. Saratchandran, "Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm," IEEE Transactions on Neural Networks, vol.9, no.2, pp. 308-318, 1998. (Pubitemid 128743638)
20. S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis function network," IEEE Transactions on Neural Networks, vol.2, no.2, pp. 302-309, 1991.
21. M. J. Er and S. Wu, "A fast learning algorithm for parsimonious fuzzy neural systems," Fuzzy Sets and Systems, vol.126, pp. 337-351, 2002. (Pubitemid 34154804)
22. S. Wu, M. J. Er, and Y. Gao, "A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks," IEEE Transactions on Fuzzy Systems, vol.9, no.4, pp. 578-594, 2001. (Pubitemid 32933044)
23. Y. Gao and M. J. Er, "Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems," IEEE Transactions on Fuzzy Systems, vol.11, no.4, pp. 12-32, 2003.
24. Y. Gao and M. J. Er, "NARMAX time series model prediction: Feedforward and recurrent fuzzy neural network approaches," Fuzzy Sets and Systems, vol.150, pp. 331-350, 2005. (Pubitemid 40056024)
25. M .J Er, F. Liu, and M. B. Li, "Channel equalization using dynamic fuzzy neural networks," International Journal of Fuzzy Systems, vol.11, no.4, pp. 10-19, 2009.
26. G. Leng, G. Prasad, and T. M. McGinnity, "An on-line algorithm for creating self-organizing fuzzy neural networks," Neural Networks, vol.17, pp. 1477-1493, 2004. (Pubitemid 39487143)
27. G. Leng and T. M. McGinnity, "Design for self-organizing fuzzy neural networks based on genetic algorithms," IEEE Transactions on Fuzzy Systems, vol.14, no.6, pp. 755-765, 2006. (Pubitemid 46432456)
28. G. B. Huang, P. Saratchandran, and N. Sundararajan, "An efficient sequential learning algorithm for growing and pruning (GAP-RBF) networks," IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol.34, pp. 2284-2292, 2004.
29. G. B. Huang, P. Saratchandran, and N. Sundararajan, "A generalized growing and pruning (GGAP-RBF) neural network for function approximation," IEEE Transactions on Neural Networks, vol.16, no.1, pp. 57-67, 2005. (Pubitemid 40241910)
30. S. Mitra and Y. Hayashi, "Neuro-fuzzy rule generation: Survey in soft computing framework," IEEE Transactions on Neural Networks, vol.11, no.3, pp. 748-768, 2000.