Cataloged from PDF version of article.Engineering design problems, especially in signal and image processing, give rise to linear least squares problems arising from discretization of some inverse problem. The associated data are typically subject to error in these applications while the computed solution may only be implemented up to limited accuracy digits, i.e., quantized. In the present paper, we advocate the use of the robust counterpart approach of Ben-Tal and Nemirovski to address these issues simultaneously. Approximate robust counterpart problems are derived, which leads to semidefinite programming problems yielding stable solutions to overdetermined systems of linear equations affected by both data uncertainty and implement...
Robust optimization is a rapidly developing methodology for handling optimization problems affected ...
We discuss the solution of numerically ill-posed overdetermined systems of equations using Tikhonov ...
The purpose of this note is to present a robust counterpart of the Huber estimation problem in the s...
Cataloged from PDF version of article.Engineering design problems, especially in signal and image pr...
AbstractEngineering design problems, especially in signal and image processing, give rise to linear ...
www.elsevier.com/locate/laa On robust solutions to linear least squares problems affected by data un...
Cataloged from PDF version of article.We study the problem of estimating an unknown deterministic si...
We study the problem of estimating an unknown deterministic signal that is observed through an unkno...
In many signal processing applications the core problem reduces to a linear system of equations. Coe...
Cataloged from PDF version of article.A novel approach is proposed to provide robust and accurate e...
Cataloged from PDF version of article.A novel approach is proposed to provide robust and accurate e...
The solution of robust counterparts of optimization problems with uncertain data is currently attrac...
Recent advances in total least squares approaches for solving various errors-in-variables modeling p...
Finding the least squares (LS) solution s to a system of linear equations Hs = y where H, y are give...
The ever growing performances of mathematical programming solvers allows to be thinking of solving m...
Robust optimization is a rapidly developing methodology for handling optimization problems affected ...
We discuss the solution of numerically ill-posed overdetermined systems of equations using Tikhonov ...
The purpose of this note is to present a robust counterpart of the Huber estimation problem in the s...
Cataloged from PDF version of article.Engineering design problems, especially in signal and image pr...
AbstractEngineering design problems, especially in signal and image processing, give rise to linear ...
www.elsevier.com/locate/laa On robust solutions to linear least squares problems affected by data un...
Cataloged from PDF version of article.We study the problem of estimating an unknown deterministic si...
We study the problem of estimating an unknown deterministic signal that is observed through an unkno...
In many signal processing applications the core problem reduces to a linear system of equations. Coe...
Cataloged from PDF version of article.A novel approach is proposed to provide robust and accurate e...
Cataloged from PDF version of article.A novel approach is proposed to provide robust and accurate e...
The solution of robust counterparts of optimization problems with uncertain data is currently attrac...
Recent advances in total least squares approaches for solving various errors-in-variables modeling p...
Finding the least squares (LS) solution s to a system of linear equations Hs = y where H, y are give...
The ever growing performances of mathematical programming solvers allows to be thinking of solving m...
Robust optimization is a rapidly developing methodology for handling optimization problems affected ...
We discuss the solution of numerically ill-posed overdetermined systems of equations using Tikhonov ...
The purpose of this note is to present a robust counterpart of the Huber estimation problem in the s...