On the Some New Preconditioned Generalized AOR Methods for Solving Weighted Linear Least Squares Problems

Abstract

Recently, in the paper [Z.G. Huang, L.G. Wang, Z. Xu, J.J. Cui, Some new preconditioned generalized AOR methods for solving weighted linear least squares problems, Computational and Applied Mathematics, 37(2018) 415-438.], Huang et al, by using the generalized accelerated over-relaxation (GAOR) methods, proposed some new preconditioners for solving weighted linear least squares problems and discuss their comparison results. In this paper, we present a new model of GAOR methods to solve the weighted linear least squares problems. We prove that the new model is superior to the existing mentioned methods. Numerical examples are also reported to confirm our theoretical analysis.

Keywords

• Preconditioned GAOR method
• weighted linear least squares problems
• linear system
• convergence
• comparison theorem