Convergence of the iterative Hammerstein system identification algorithm

The convergence of the iterative identification algorithm for the Hammerstein system has been an open problem for a long time. In this paper, a detailed study is carried out and various convergence properties of the iterative algorithm are derived. It is shown that the iterative algorithm with norma...

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Veröffentlicht in:	IEEE transactions on automatic control 2004-11, Vol.49 (11), p.1929-1940
Hauptverfasser:	Bai, E.-W., Li, D.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Automatic control Computer science control theory systems Control theory. Systems Convergence Exact sciences and technology Frequency domain analysis Hammerstein systems Iterative algorithms Iterative methods Least squares method Least squares methods Modelling and identification Nonlinear dynamical systems Nonlinear systems Parameter estimation Stochastic processes System identification
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Zusammenfassung:	The convergence of the iterative identification algorithm for the Hammerstein system has been an open problem for a long time. In this paper, a detailed study is carried out and various convergence properties of the iterative algorithm are derived. It is shown that the iterative algorithm with normalization is convergent in general. Moreover, it is shown that convergence takes place in one step (two least squares iterations) for finite-impulse response Hammerstein models with i.i.d. inputs.
ISSN:	0018-9286 1558-2523
DOI:	10.1109/TAC.2004.837592