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This paper has proposed the GMRES that augments Krylov subspaces with a set of approximate right singular vectors. The proposed method suppresses the error norms of a linear system of equations. Numerical experiments comparing the proposed…

Numerical Analysis · Mathematics 2019-02-07 Mashetti Ravibabu

The main goal of this paper is to propose a new quaternion total variation regularization model for solving linear ill-posed quaternion inverse problems, which arise from three-dimensional signal filtering or color image processing. The…

Numerical Analysis · Mathematics 2024-08-07 Xuan Liu , Zhigang Jia , Xiaoqing Jin

The GMRES algorithm of Saad and Schultz (1986) is an iterative method for approximately solving linear systems $A{\bf x}={\bf b}$, with initial guess ${\bf x}_0$ and residual ${\bf r}_0 = {\bf b} - A{\bf x}_0$. The algorithm employs the…

Numerical Analysis · Mathematics 2023-03-22 Stephen Thomas , Erin Carson , Miro Rozložník , Arielle Carr , Kasia Świrydowicz

{In [X. L. Lin, M. K. Ng, and Y. Zhi. {\it J. Comput. Phys.}, 434 (2021), pp. 110221] and [Y. L. Zhao, J. Wu, X. M. Gu, and H. Li. {\it Comput. Math. Appl.}, 148(2023), pp. 200--210]}, two-sided preconditioning techniques are proposed for…

Numerical Analysis · Mathematics 2024-04-23 Xuelei Lin , Jiamei Dong , Sean Hon

The inverse of a large matrix can often be accurately approximated by a polynomial of degree significantly lower than the order of the matrix. The iteration polynomial generated by a run of the GMRES algorithm is a good candidate, and its…

Numerical Analysis · Mathematics 2025-02-26 Mark Embree , Joel A. Henningsen , Jordan Jackson , Ronald B. Morgan

We introduce an iterative method named GPMR for solving 2x2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously two rectangular matrices to upper Hessenberg form and that is closely related to the…

Numerical Analysis · Mathematics 2021-11-16 Alexis Montoison , Dominique Orban

Low rank matrix recovery problems, including matrix completion and matrix sensing, appear in a broad range of applications. In this work we present GNMR -- an extremely simple iterative algorithm for low rank matrix recovery, based on a…

Optimization and Control · Mathematics 2022-04-28 Pini Zilber , Boaz Nadler

In this work, we develop an alternating nonlinear Generalized Minimum Residual (NGMRES) algorithm with depth $m$ and periodicity $p$, denoted by aNGMRES($m, p$), applied to linear systems. We provide a theoretical analysis to quantify by…

Numerical Analysis · Mathematics 2025-10-31 Yunhui He

Many Krylov subspace methods for shifted linear systems take advantage of the invariance of the Krylov subspace under a shift of the matrix. However, exploiting this fact in the non-Hermitian case introduces restrictions; e.g., initial…

Numerical Analysis · Mathematics 2016-02-05 Kirk M. Soodhalter

The paper discusses the efficiency of the classical BiCGStab method and several of its modifications for solving systems with multiple right-hand side vectors. These iterative methods are widely used for solving systems with large sparse…

Numerical Analysis · Mathematics 2019-12-17 Boris Krasnopolsky

An implementation of GMRES with multiple preconditioners (MPGMRES) is proposed for solving shifted linear systems with shift-and-invert preconditioners. With this type of preconditioner, the Krylov subspace can be built without requiring…

Numerical Analysis · Mathematics 2016-03-31 Tania Bakhos , Peter Kitanidis , Scott Ladenheim , Arvind K. Saibaba , Daniel Szyld

This paper addresses multilinear systems of equations which arise in various applications such as data mining and numerical partial differential equations. When the multilinear system under consideration involves a nonsingular…

Optimization and Control · Mathematics 2019-05-14 Xueli Bai , Hongjin He , Chen Ling , Guanglu Zhou

Inverse problems arise in various scientific and engineering applications, necessitating robust numerical methods for their solution. In this work, we consider the effectiveness of Krylov subspace iterative methods, including GMRES, QMR,…

Numerical Analysis · Mathematics 2025-08-11 Moshen Hu , Lucas Onisk

A deflated and restarted Lanczos algorithm to solve hermitian linear systems, and at the same time compute eigenvalues and eigenvectors for application to multiple right-hand sides, is described. For the first right-hand side, eigenvectors…

High Energy Physics - Lattice · Physics 2010-01-21 Abdou M. Abdel-Rehim , Ronald B. Morgan , Dywayne Nicely , Walter Wilcox

Polynomial convergence bounds are considered for left, right, and split preconditioned GMRES. They include the cases of Weighted and Deflated GMRES for a linear system Ax = b. In particular, the case of positive definite A is considered.…

Numerical Analysis · Mathematics 2025-10-03 Nicole Spillane , Daniel B Szyld

Of all the possible projection methods for solving large-scale Lyapunov matrix equations, Galerkin approaches remain much more popular than minimal-residual ones. This is mainly due to the different nature of the projected problems stemming…

Numerical Analysis · Mathematics 2024-03-06 Kathryn Lund , Davide Palitta

A general asynchronous alternating iterative model is designed, for which convergence is theoretically ensured both under classical spectral radius bound and, then, for a classical class of matrix splittings for $\mathsf H$-matrices. The…

Numerical Analysis · Mathematics 2023-12-29 Guillaume Gbikpi-Benissan , Qinmeng Zou , Frédéric Magoulès

We explore the use of flexible GMRES as an outer wrapper for sketched GMRES. Building on a new bound for the residual of FGMRES in terms of the residual of the preconditioner, we derive a practical randomized solver that requires very…

Numerical Analysis · Mathematics 2026-05-11 Stefan Güttel , John W. Pearson

We introduce a family of numerical algorithms for the solution of linear system in higher dimensions with the matrix and right hand side given and the solution sought in the tensor train format. The proposed methods are rank--adaptive and…

Numerical Analysis · Mathematics 2014-10-07 Sergey V. Dolgov , Dmitry V. Savostyanov

We develop a novel randomized conjugate gradient least squares (RCGLS) method for solving least-squares problems, in which iterative sketching is employed at each step to reduce the dimension and hence the computational cost. In particular,…

Numerical Analysis · Mathematics 2026-05-26 Yun Zeng , Jian-Feng Cai , Deren Han , Jiaxin Xie