Recursive estimation on spatially rearranged data for dynamic order determination and nonlinear component detection

Proceedings of the American Control Conference

Volumn , Issue , 2009, Pages 4398-4403

  Su, Ming ^a   Rhinehart, R Russell ^a  

^a Oklahoma State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC ORDER; FINAL PREDICTION ERRORS; MODEL PARAMETERS; NEAREST NEIGHBORS; NON-LINEAR SYSTEM IDENTIFICATION; NON-LINEARITY; NONLINEAR COMPONENTS; ORDER DETERMINATION; PARAMETER VARIATION; RECURSIVE ESTIMATION; SYSTEM IDENTIFICATIONS; SYSTEM STRUCTURES;

MOBILE TELECOMMUNICATION SYSTEMS; NONLINEAR SYSTEMS; RECURSIVE FUNCTIONS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 70449646320     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACC.2009.5160377     Document Type: Conference Paper

References (11)

1. nd, New York: Springer, 1998.
2. A.J. Miller, "Subset selection in regression", New York: Chapman And Hall, 1990, pp 43-83.
3. I. Lind and L. Liung, " Regressor and structure selection in NARX models using a structured ANOVA approach", Automatica, vol. 44, 2008, pp 383-395.
4. C. Molina, N. Sampson, W. J. Fitzgerald, and M. Niranjan, "Geometric techniques for finding the embedding dimension of time series", Neural Networks for signal processing [1996] VI. Proceedings of the 1996 IEEE signal processing society workshop, vol. 1, no. 4-6, Sep 1996, pp 161 - 169.
5. C. Rhodes and M. Morari, "Determining the model order of nonlinear input/output systems directly from data", Proceedings of the American Control Conference 1995, vol. 3, no. 21-23, June 1995, pp 2190 - 2194
6. X. He and H. Asada, "A new method for identifying orders of input-output models for nonlinear dynamic systems", Proceedings of the American Control Conference, June 1993, pp 2520 - 2523
7. P. Young, "Recursive estimation and time-series analysis: An introduction", New York: Springer-Verlag, 1984.
8. L. Ljung and T. Soderstrm, "Theory and practice of recursive identification", New York: MIT Press, 1987.
9. P. Young, "Time variable and state dependent modeling of non-stationary and nonlinear time series", in Developments in time series analysis, T.S Rao, Ed. New York: Chapman and Hall, 1993, pp 374-413.
10. nd, New York: Prentice Hall PTR, 1999.
11. K.S. Narendra and K. Parthasarathy, "Identification and control of dynamical systems using neural networks", IEEE transactions on neural network, vol. 1, no.1, March 1990, pp 4-27.