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).
REFERENCES
Åström K.J. and P. Eykhoff (1971). System
identification—a survey. Automatica, Vol. 7, pp. 123-
167.
Åström K.J. and Bohlin (1965), Numerical identification of
linear dynamic systems from normal operating records.
IFAC Symposium on Self-Adaptive Systems,
Teddington, England.
Ding, F. and T. Chen (2007). Performance analysis of multiinnovation
gradient type identification methods.
Automatica, Vol. 43, pp. 1-14.
Furht, B.P. (1973). New estimator for the identification of
dynamic processes. IBK Report. Institute Boris Kidric
Vinca, Belgrade, Yugoslava.
Goodwin, G.C. and K.S. Sin (1984). Adaptive filtering,
prediction and control. Englewood Cliffs, NJ: Prentice-
Hall.
Ghirmai, T. and J. H. Kotecha and P. M. Djuric (2004).
Blind equalization for time–varying channels and
multiple samples processing using particle filtering.
Digital Signal Processing, Vol. 14, pp.312-331.
Gratton, S., A.S. Lawless, and N.K. Nichols (2007).
Approximate Gauss-Newton methods for nonlinear least
squares problem. SIAM J. Optim., Vol. 18, No. 1, pp106-
132.
Han, K., Y.C. Zhu, Z.H. Xu, J. Zhao and J.X. Qian (2008).
Disturbance reduction in MPC using an adaptive
disturbance model. To be submitted.
Ljung, L. (1999). System identification: Theory for the
user(2nd ed.). Englewood Cliffs, NJ: Prentice-Hall.
Ljung, L. and T. Söderström (1983). Theory and practice of
recursive identification. The MIT Press.
Ljung, L. (1978). Convergence analysis of parametric
identification methods. IEEE Transactions on
Automatic Control, Vol. AC-23, pp. 770-783.
Moore, J.B. and G. Ledwich (1980). Multivariable adaptive
parameter and state estimators with convergence
analysis. Journal of the Australian Mathematical
society, Vol. 21, pp. 176-197.
Neveu, J. (1975). Discrete Parameter Martingales. North-
Holland, Amsterdam.
荷兰埃因霍温理工大学电气工程论文定制Oruç, S. (2007). Multi-sample and multi-iterative recursive
https://www.51lunwen.org/hllw/2011/0706/1208206071.htmlleast squares method and recursive output error method.
Internship Report No. 07S/04, Dept. of EE, Eindhoven
University of Technology.
Panuska,V. (1968). A stochastic approximation method for
identification of linear systems using adaptive filtering.
Proc. JACC.
Solo,V.(1978). Time series recursions and stochastic
approximation. PhD dissertation, The Australian
National University, Canberra, Australia.
Young, P.C. (1968). The use of linear regression and related
procedures for the identification of dynamic processes.
Proc.7th IEEE Symposium on Adaptive Processes,
UCLA.
Zhu, Y.C. (2001). Multivariable System Identification for
Process Control. Elsevier Science, Oxford.
449

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