Abstract
We present fast algorithms and their stability properties for Toeplitz structured total least squares (STLS) problems.
The STLS problem can be formulated as the following constrained optimization problem
This natural extension of the TLS problem is clearly more difficult to solve than the TLS problem, because of its highly nonlinear nature and the existence of many local minima. We focus here on the frequently occurring case where [A b] is a Toeplitz matrix. The problem is solved in an iterative fashion, in which at each iteration the Karush-Kuhn-Tucker (KKT) equations of the locally linearized problem have to be solved. For this kernel routine we use a generalized Schur decomposition algorithm based on the low displacement rank of the KKT system matrix. By exploiting the sparsity of the associated generators, we obtain a fast algorithm that requires O(mn + n 2) flops per iteration, where m and n are the number of rows and the number of columns of A, respectively. We also prove the stability of the latter kernel routine. The efficiency of the proposed fast implementation is compared to the efficiency of the straightforward implementation, which does not exploit the structure of the involved matrices. The comparison is done on a recently introduced speech compression scheme in which the considered STLS problem constitutes one of the kernel problems. The numerical results confirm the high efficiency of the newly proposed fast implementation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
E. Anderson, Z. Bai, C. Bischof, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, S. Ostrouchov, and D. Sorensen. LAPACK Users’ Guide. SIAM, Philadelphia, 1995.
E. Anderson, Z. Bai, and J. J. Dongarra. Generalized QR factorization and its applications. Technical Report CS-91–131 (LAPACK Working Note 31 ), Computer Science Dept., University of Tennessee, Knoxville, 1991.
A.W. Bojanczyk, R.P. Brent, P. Van Dooren and F.R. De Hoog, A note on downdating the Cholesky factorization, SIAM J. Sci. Stat. Comput., 1:210–220, 1980.
S. Chandrasekaran, A.H. Sayed, Stabilizing the generalized Schur algorithm, SIAM J. Matrix Anal. Appl., 17 (4): 950–983, 1996.
G.H. Golub and C.F. Van Loan. Matrix Computations. Johns Hopkins University Press, Baltimore, 1989.
T. Kailath, S. Kung and M. Morf, Displacement ranks of matrices and linear equations, J. Math. Anal. Appl., 68: 395–407, 1979.
T. Kailath, Displacement structure and array algorithms, in Fast Reliable Algorithms for Matrices with Structure, T. Kailath and A. H. Sayed, Ed., SIAM, Philadelphia, 1999.
T. Kailath, A.H. Sayed, Displacement structure: Theory and applications, SIAM Review, 37: 297–386, 1995.
P. Lemmerling, I. Dologlou, and S. Van Huffel, Speech compression based on exact modeling and structured total least norm optimization, in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP’98), Vol. 1, Seattle, WA, 353–356, 1998.
P. Lemmerling, N. Mastronardi and S. Van Huffel, Fast algorithm for solving the Hankel/Toeplitz structured total least squares problem, Numerical Algorithms, 23: 371–392, 2000.
P. Lemmerling, N. Mastronardi and S. Van Huffel, Fast algorithms for structured total least squares in speech compression, Internal Report 01–55, ESAT-SISTA, K.U.Leuven (Leuven, Belgium ), 2001.
P. Lemmerling and S. Van Huffel, Structured total least squares: analysis, algorithms and applications, in this volume.
L. Ljung, System identification: theory for the user. Prentice-Hall, Inc., 1987.
N. Mastronardi, P. Lemmerling and S. Van Huffel, Fast structured total least squares algorithm for solving the basic deconvolution problem, SIAM J. Matrix Anal. Appl., 22 (2): 533–553, 2000.
N. Mastronardi, P. Van Dooren, and S. Van Huffel, On the stability of the generalized Schur algorithm, Proceedings of the conference Numerical Analysis and Its Applications, Rousse, Bulgaria, June 2000. Lecture Notes in Computer Science, 560–567, 1988, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Mastronardi, N., Lemmerling, P., Van Huffel, S. (2002). Fast Structured Total Least Squares Algorithms via Exploitation of the Displacement Structure. In: Van Huffel, S., Lemmerling, P. (eds) Total Least Squares and Errors-in-Variables Modeling. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3552-0_9
Download citation
DOI: https://doi.org/10.1007/978-94-017-3552-0_9
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5957-4
Online ISBN: 978-94-017-3552-0
eBook Packages: Springer Book Archive