GMRES on singular systems revisited

09/01/2020
by   Ken Hayami, et al.
0

In [Hayami K, Sugihara M. Numer Linear Algebra Appl. 2011; 18:449–469], the authors analyzed the convergence behaviour of the Generalized Minimal Residual (GMRES) method for the least squares problem min_ x∈ R^n b - A x_2^2, where A ∈ R^n × n may be singular and b∈ R^n, by decomposing the algorithm into the range R(A) and its orthogonal complement R(A)^⊥ components. However, we found that the proof of the fact that GMRES gives a least squares solution if R(A) = R(A^ T ) was not complete. In this paper, we will give a complete proof.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/24/2020

Computing singular elements modulo squares

The group of singular elements was first introduced by Helmut Hasse and ...
research
07/28/2017

The Convergence of Least-Squares Progressive Iterative Approximation with Singular Iterative Matrix

Developed in [Deng and Lin, 2014], Least-Squares Progressive Iterative A...
research
01/27/2022

GMRES using pseudo-inverse for range symmetric singular systems

Consider solving large sparse range symmetric singular linear systems A ...
research
02/22/2016

Sparse Linear Regression via Generalized Orthogonal Least-Squares

Sparse linear regression, which entails finding a sparse solution to an ...
research
12/20/2021

Consistency and Rate of Convergence of Switched Least Squares System Identification for Autonomous Switched Linear Systems

In this paper, we investigate the problem of system identification for a...
research
05/30/2023

Mixed Precision Rayleigh Quotient Iteration for Total Least Squares Problems

With the recent emergence of mixed precision hardware, there has been a ...
research
05/12/2023

Levenberg-Marquardt method with Singular Scaling and applications

Inspired by certain regularization techniques for linear inverse problem...

Please sign up or login with your details

Forgot password? Click here to reset