Abstract In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems
In this paper we study how to update the solution of the linear system Ax = b after the matrix A is ...
Residual statics corrections can be formulated as a linear inverse problem. Usually, solving this pr...
This paper discussed QR factorization algorithms for a special type of matrix arising from the appli...
We consider a repeated QR updating algorithm for the solution of equality constrained linear least s...
The weighting method for solving a least squares problem with linear equality constraints multiplies...
The null space method is a standard method for solving the linear least squares problem subject to e...
The purpose of this note is to re-introduce the generalized QR factorization with or without pivotin...
Abstract. It is well known that the solution of the equality constrained least squares (LSE) problem...
It is well known that the solution of the equality constrained least squares (LSE) problem min Bx=d ...
. In 1980, Han [6] described a finitely terminating algorithm for solving a system Ax b of linear ...
AbstractThe purpose of this paper is to reintroduce the generalized QR factorization with or without...
We address the problem of solving linear least-squares problems min——Ax−b—— when A is a sparse m-by-...
SIGLEAvailable from British Library Document Supply Centre-DSC:6184.6725(301) / BLDSC - British Libr...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
A backward error analysis of the direct elimination method for linear equality constrained least squ...
In this paper we study how to update the solution of the linear system Ax = b after the matrix A is ...
Residual statics corrections can be formulated as a linear inverse problem. Usually, solving this pr...
This paper discussed QR factorization algorithms for a special type of matrix arising from the appli...
We consider a repeated QR updating algorithm for the solution of equality constrained linear least s...
The weighting method for solving a least squares problem with linear equality constraints multiplies...
The null space method is a standard method for solving the linear least squares problem subject to e...
The purpose of this note is to re-introduce the generalized QR factorization with or without pivotin...
Abstract. It is well known that the solution of the equality constrained least squares (LSE) problem...
It is well known that the solution of the equality constrained least squares (LSE) problem min Bx=d ...
. In 1980, Han [6] described a finitely terminating algorithm for solving a system Ax b of linear ...
AbstractThe purpose of this paper is to reintroduce the generalized QR factorization with or without...
We address the problem of solving linear least-squares problems min——Ax−b—— when A is a sparse m-by-...
SIGLEAvailable from British Library Document Supply Centre-DSC:6184.6725(301) / BLDSC - British Libr...
The solution of nearly square overdetermined linear systems is studied. The sparse QR technique is c...
A backward error analysis of the direct elimination method for linear equality constrained least squ...
In this paper we study how to update the solution of the linear system Ax = b after the matrix A is ...
Residual statics corrections can be formulated as a linear inverse problem. Usually, solving this pr...
This paper discussed QR factorization algorithms for a special type of matrix arising from the appli...