PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Total Least Squares Methods
I Markovsky, D Sima and S Van Huffel
In: Wiley Interdisciplinary Reviews: Computational Statistics Computational Statistics . (2009) Wiley .

Abstract

Recent advances in total least squares approaches for solving various errors-in-variables modeling problems are reviewed, with emphasis on the following generalizations: 1. the use of weighted norms as a measure of the data perturbation size, capturing prior knowledge about uncertainty in the data; 2. the addition of constraints on the perturbation to preserve the structure of the data matrix, motivated by structured data matrices occurring in signal and image processing, systems and control, and computer algebra; 3. the use of regularization in the problem formulation, aiming at stabilizing the solution by decreasing the effect due to intrinsic ill-conditioning of certain problems.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5719
Deposited By:Ivan Markovsky
Deposited On:08 March 2010