Structure selective updating for nonlinear models and radial basis function neural networks

International Journal of Adaptive Control and Signal Processing

Volumn 12, Issue 4, 1998, Pages 325-345

  Luo, W ^a   Billings, S A ^b  

^a Dental Health Alliance   (United States)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Adaptive structure detection; Neural networks; On line processing; System identification

Indexed keywords

ADAPTIVE ALGORITHMS; COMPUTATIONAL COMPLEXITY; MATHEMATICAL MODELS; NEURAL NETWORKS; ONLINE SYSTEMS; PARAMETER ESTIMATION; REGRESSION ANALYSIS; VECTORS;

ADAPTIVE STRUCTURE DETECTIONS; NONLINEAR MODEL STRUCTURES; ONLINE MODEL MODIFICATIONS; RADIAL BASIS FUNCTION NEURAL NETWORKS;

ADAPTIVE CONTROL SYSTEMS;

EID: 0032098522     PISSN: 08906327     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1099-1115(199806)12:4<325::AID-ACS492>3.0.CO;2-Q     Document Type: Article

References (22)

1. Bellanger, M. G., Adaptive Filters and Signal Analysis, Marcel-Dekker, New York, 1988.
2. Friedlander, B., 'Lattice filters for adaptive processing', Proc. IEEE, 70, 829-867 (1982).
3. Luo, W., S. A. Billings and K. M. Tsang, 'On-line structure detection and parameter estimation with exponential windowing for nonlinear systems', submitted for publication.
4. Luo, W. and S. A. Billings, 'Adaptive model selection and estimation for nonlinear systems using a sliding data window', Signal Processing, 46, 179-202 (1995).
5. Billings, S. A. and S. Chen, 'Extended model set, global data and threshed model identification of severely nonlinear systems', Int, J. Control, 50, 1897-1923 (1989)
6. Leontaritis, I. J. and S. A. Billings, Input-output parametric models for nonlinear systems, Part I: Deterministic nonlinear systems; Part II: Stochastic nonlinear systems', Int. J. Control, 41, 303-344 (1985).
7. Gentleman, W. M., 'Least squares computation by Givens transformation without square roots', J. Inst. Math. and Appl., 12, 329-336 (1973).
8. Gentleman, W. M., 'Regression problems and the QR decomposition', Bull. Inst. Math. Appl., 10, 195-197 (1974).
9. Liu, Y. P., M. J. Korenberg, S. A. Billings and M. B. Fadzil, 'The non-linear identification of a heat exchanger', 26th IEEE Conf. on Decision and Control, 9-11 Dec. 1987, Los Angeles, U.S.A.
10. Clarke, D. and P. J. Gawthrop, 'Self-tuning controller', Proc. Inst. Elec. Engng., 122, 929-934 (1975).
11. Broomhead, D. S. and D. Lowe, 'Multivariable functional interpolation and adpative networks', Complex Systems, 2, 321-355 (1988).
12. Poggio, T. and F. Girosi, 'Networks for application and learning', Proc. IEEE, 78, 1481-1496 (1990).
13. Chen, S. and S. A. Billings, C. F. N. Cowan and P. M. Grant, 'Non-linear system identification using radial basis functions', Int, J. Systems Sci., 21, 2513-2539 (1990).
14. Chen, S., S. A. Billings, C. F. N. Cowan and P. M. Grant, 'Practical identification of NARMAX models using radial basis functions', Int. J. Control, 52, 1327-1350 (1990).
15. Leonard, J. A. and M. A. Kramer, 'Radial basis function networks for classifying process faults', IEEE Control Systems Mag. 31-38 (1991).
16. Park, J. and I. W. Sandberg, 'Universal approximation using radial basis function networks', Neural Computation, 3, 246-257 (1991).
17. Billings, S. A. and S. Chen, 'Neural networks and system identification', in K. Warwick, G. W. Irwin and K. J. Hunt (eds), Neural Networks for Control and Systems, P. Peregrinus, London, 1992, pp. 181-205.
18. Chen, S., S. A. Billings and P. M. Grant, 'Recursive hybrid algorithm for nonlinear system identification using radial basis function networks', Int. J. Control, 55, 1051-1070 (1992).
19. Billings, S. A. and C. F. Fung, 'Recurrent radial basis function networks for adaptive noise cancellation', J. Neural Networks, 8, 273-290 (1995).
20. Chen, S. and S. A. Billings, 'Recursive prediction error parameter estimator for nonlinear models', Int. J. Control, 49, 569-594 (1989).
21. Chen, S., S. A. Billings and W. Luo, 'Orthogonal least squared methods and their application to non-linear system identification', Int. J. Control, 50, 1873-1896 (1989).
22. Girosi, F. and T. Poggio, 'Networks and the best approximation property', Biol. Cybernet. 63, 169-179 (1990).