Persistency of excitation in identification using radial basis function approximants

In this paper, identification algorithms whose convergence and rate of convergence hinge on the regressor vector being persistently exciting are discussed. It is then shown that if the regressor vector is constructed out of radial basis function approximants, it will be persistently exciting, provid...

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Veröffentlicht in:	SIAM journal on control and optimization 1995-03, Vol.33 (2), p.625-642
Hauptverfasser:	KURDILA, A. J, NARCOWICH, F. J, WARD, J. D
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Approximation Computer science control theory systems Control theory. Systems Exact sciences and technology Identification Modelling and identification Neural networks
Online-Zugang:	Volltext
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