Model order determination using the Hankel matrix of impulse responses

Applied Mathematics Letters

Volumn 24, Issue 5, 2011, Pages 797-802

  Yin, Huanhuan ^a   Zhu, Zhifang ^a   Ding, Feng ^a  

^a JIANGNAN UNIVERSITY   (China)

Author keywords

Hankel matrix; Order determination; Order identification; Singular value decomposition (SVD)

Indexed keywords

HANKEL MATRIX; IDENTIFICATION METHOD; IDENTIFICATION PROBLEM; MODEL ORDER; MODEL ORDER DETERMINATION; NUMERICAL EXAMPLE; ORDER DETERMINATION; ORDER IDENTIFICATION;

NUMERICAL METHODS;

SINGULAR VALUE DECOMPOSITION;

EID: 79551488650     PISSN: 08939659     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aml.2010.12.046     Document Type: Article

References (24)

1. F. Ding, and T. Chen Performance analysis of multi-innovation gradient type identification methods Automatica 43 1 2007 1 14
2. F. Ding, P.X. Liu, and G. Liu Auxiliary model based multi-innovation extended stochastic gradient parameter estimation with colored measurement noises Signal Processing 89 10 2009 1883 1890
3. L.L. Han, and F. Ding Multi-innovation stochastic gradient algorithms for multi-input multi-output systems Digital Signal Processing 19 4 2009 545 554
4. J.B. Zhang, F. Ding, and Y. Shi Self-tuning control based on multi-innovation stochastic gradient parameter estimation Systems & Control Letters 58 1 2009 69 75
5. F. Ding Several multi-innovation identification methods Digital Signal Processing 20 4 2010 1027 1039
6. D.Q. Wang, and F. Ding Performance analysis of the auxiliary models based multi-innovation stochastic gradient estimation algorithm for output error systems Digital Signal Processing 20 3 2010 750 762
7. F. Ding, P.X Liu, and G. Liu Multi-innovation least squares identification for system modeling IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 40 3 2010 767 778
8. F. Ding, P.X. Liu, and G. Liu Gradient based and least-squares based iterative identification methods for OE and OEMA systems Digital Signal Processing 20 3 2010 664 677
9. Y.J. Liu, D.Q. Wang, and F. Ding Least-squares based iterative algorithms for identifying BoxJenkins models with finite measurement data Digital Signal Processing 20 5 2010 1458 1467
10. D.Q. Wang, and F. Ding Inputoutput data filtering based recursive least squares identification for CARARMA systems Digital Signal Processing 20 4 2010 991 999
11. D.Q. Wang, and F. Ding Extended stochastic gradient identification algorithms for HammersteinWiener ARMAX systems Computers & Mathematics with Applications 56 12 2008 3157 3164
12. F. Ding, G. Liu, and X.P. Liu Partially coupled stochastic gradient identification methods for non-uniformly sampled systems IEEE Transactions on Automatic Control 55 8 2010 1976 1981
13. J. Ding, Y. Shi, H.G. Wang, and F. Ding A modified stochastic gradient based parameter estimation algorithm for dual-rate sampled-data systems Digital Signal Processing 20 4 2010 1238 1249
14. F. Ding, P.X. Liu, and G. Liu Identification methods for Hammerstein nonlinear systems Digital Signal Processing 2011 10.1016/j.dsp.2010.06.006
15. H.N. Duong, and I.D. Landau An IV based criterion for model order selection Automatica 32 6 1996 909 914
16. D. Bauer Order estimation for subspace methods Automatica 37 10 2001 1561 1573
17. J. Schoukens, Y. Rolain, and R. Pintelon Modified AIC rule for model selection in combination with prior estimated noise models Automatica 38 5 2002 903 906
18. R.Y. Ruan, C.L. Yang, H.X. Chen, and B. Li On-line order estimation and parameter identification for linear stochastic feedback control systems (CARMA model) Automatica 39 2 2003 243 253
19. I. Lind, and L. Ljung Regressor selection with the analysis of variance method Automatica 41 4 2005 693 700
20. C.H. Aladag, E. Egrioglu, and C. Kadilar Forecasting nonlinear time series with a hybrid methodology Applied Mathematics Letters 22 9 2009 1467 1470
21. A. Thavaneswaran, S.S. Appadoo, and M. Ghahramani RCA models with GARCH innovations Applied Mathematics Letters 22 1 2009 110 114
22. H. Gong, and A. Thavaneswaran Recursive estimation for continuous time stochastic volatility models Applied Mathematics Letters 22 11 2009 1770 1774
23. F. Ding, and J. Ding Least squares parameter estimation with irregularly missing data International Journal of Adaptive Control and Signal Processing 24 7 2010 540 553
24. F. Ding, L. Qiu, and T. Chen Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems Automatica 45 2 2009 324 332