Journal of computational and applied mathematics vol:132 issue:1 pages:71-81
Two recent approaches (Van Overschee, De Moor, N4SID, Automatica 30 (1) (1994) 75; Verhaegen, Int. J. Control 58(3) (1993) 555) in subspace identification problems require the computation of the R factor of the QR factorization of a block-Hankel matrix H, which, in general has a huge number of rows. Since the data are perturbed by noise, the involved matrix H is, in general, full rank. It is well known that, from a theoretical point of view. the R factor of the PR factorization of H is equivalent to the Cholesky factor of the correlation matrix HTH, apart from a multiplication by a sign matrix. In Sima (Proceedings Second NICONET Workshop, Paris-Versailles, December 3, 1999, p. 75), a fast Cholesky factorization of the correlation matrix, exploiting the block-Hankel structure of H, is described. In this paper we consider a fast algorithm to compute the R factor based on the generalized Schur algorithm. The proposed algorithm allows to handle the rank-deficient case. (C) 2001 Elsevier Science B.V. All rights reserved.