Result: The matrix-restricted total least-squares problem

Title:
The matrix-restricted total least-squares problem
Authors:
Source:
Signal processing. 87(10):2303-2312
Publisher Information:
Amsterdam: Elsevier Science, 2007.
Publication Year:
2007
Physical Description:
print, 20 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Industrial Engineering and Management, Technion-Israel Institute of Technology, Haifa 32000, Israel
ISSN:
0165-1684
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Telecommunications and information theory
Accession Number:
edscal.19121995
Database:
PASCAL Archive

Further Information

We present and study the matrix-restricted total least squares (MRTLS) devised to solve linear systems of the form Ax ≈ b where A and b are both subjected to noise and A has errors of the form DEC. D and C are known matrices and E is unknown. We show that the MRTLS problem amounts to solving a problem of minimizing a sum of fractional quadratic terms and a quadratic function and compare it to the related restricted TLS problem of Van Huffel and Zha [The restricted total least squares problem: formulation, algorithm, and properties, SIAM J. Matrix Anal. Appl. 12(2) (1991) 292-309.]. Finally, we present an algorithm for solving the MRTLS, which is based on a reduction to a single-variable minimization problem. This reduction is shown to have the ability of eliminating local optima points.