Comparison of traditional and neural network approaches to stochastic nonlinear system identification

KSME International Journal

Volumn 11, Issue 3, 1997, Pages 267-278

  Chong, Kil To ^a   Parlos, Alexander G ^b  

^a Chonbuk National University   (South Korea)

^b Department of Electrical and Computer Engineering   (United States)

Author keywords

Autoregressive exogeneous input model; Neural networks; Nonlinear autoregressive exogeneous input model; System identification

Indexed keywords

EID: 0000647182     PISSN: 12264865     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02946319     Document Type: Article

References (4)

1. Billings, S. S., Chen, S. and Korenberg, 1989, "Identification of MIMO Nonlinear Systems Using a Forward-regression Orthogonal Estimator," Int. J. Control, Vol. 49, pp. 2157-2189.
2. Chen, S. and Billings, S. S., 1989, "Orthogonal Least Square Methods and their Application to Nonlinear System Identification," Int. J. Control, Vol. 50, No. 5, pp. 1873-1896.
3. Chen, S. and Billings, S. S., 1989, "Modeling and Analysis of Nonlinear Time Series," Int. J. Control, Vol. 50, No. 6, pp. 2151-2171.
4. Chong, K. T., 1993, "Nonlinear System Identification Using Recurrent Neural Networks," PhD Dissertation, Texas A&M University, College Station, Tx, May.