Numerical study on incomplete orthogonal factorization preconditioners
Journal of Computational and Applied Mathematics
A new method for computing Moore-Penrose inverse matrices
Journal of Computational and Applied Mathematics
Greville's method for preconditioning least squares problems
Advances in Computational Mathematics
GMRES Methods for Least Squares Problems
SIAM Journal on Matrix Analysis and Applications
Efficient Preconditioner Updates for Shifted Linear Systems
SIAM Journal on Scientific Computing
Numerical Algorithms
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This paper describes a technique for constructing robust preconditioners for the CGLS method applied to the solution of large and sparse least squares problems. The algorithm computes an incomplete LDLT factorization of the normal equations matrix without the need to form the normal matrix itself. The preconditioner is reliable (pivot breakdowns cannot occur) and has low intermediate storage requirements. Numerical experiments illustrating the performance of the preconditioner are presented. A comparison with incomplete QR preconditioners is also included.