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We consider the solution of systems of linear algebraic equations (SLAEs) with an ill-conditioned or degenerate exact matrix and an approximate right-hand side. An approach to solving such a problem is proposed and justified, which makes it…

Numerical Analysis · Mathematics 2024-05-08 A. S. Leonov

We deal with interval parametric systems of linear equations and the goal is to solve such systems, which basically comes down to finding an enclosure for a parametric solution set. Obviously we want this enclosure to be as tight as…

Numerical Analysis · Mathematics 2025-10-07 Iwona Skalna , Milan Hladík

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work,…

Information Theory · Computer Science 2017-01-11 Mohamed Suliman , Tarig Ballal , Tareq Y. Al-Naffouri

This work considers special types of interval linear systems - overdetermined systems. Simply said these systems have more equations than variables. The solution set of an interval linear system is a collection of all solutions of all…

Numerical Analysis · Computer Science 2013-04-18 Jaroslav Horáček , Milan Hladík

We consider the problem of stabilization of a linear system, under state and control constraints, and subject to bounded disturbances and unknown parameters in the state matrix. First, using a simple least square solution and available…

Systems and Control · Electrical Eng. & Systems 2020-07-22 Edouard Leurent , Denis Efimov , Odalric-Ambrym Maillard

We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of equations in which the coefficient matrix is symmetric and indefinite with relatively small number of negative eigenvalues. The proposed…

Numerical Analysis · Computer Science 2019-01-29 Murat Manguoglu , Volker Mehrmann

Recently, inverse problems have attracted more and more attention in computational mathematics and become increasingly important in engineering applications. After the discretization, many of inverse problems are reduced to linear systems.…

Numerical Analysis · Mathematics 2022-04-07 Gong Rongfang , Huang Qin

In this paper we investigate an adaptive discretization strategy for ill-posed linear prob- lems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a…

Numerical Analysis · Mathematics 2014-07-22 Wolfgang Erb , Evgeniya V. Semenova

In this article we study the problem of recovering the unknown solution of a linear ill-posed problem, via iterative regularization methods. We review the problem of projection-regularization from a statistical point of view. A basic…

Statistics Theory · Mathematics 2007-06-13 Ana K. Fermin , Carenne Ludena

This paper develops the preconditioning technique as a method to address the accuracy issue caused by ill-conditioning. Given a preconditioner $M$ for an ill-conditioned linear system $Ax=b$, we show that, if the inverse of the…

Numerical Analysis · Mathematics 2017-05-15 Qiang Ye

For solving linear ill-posed problems regularization methods are required when the right hand side is with some noise. In the present paper regularized solutions are obtained by implicit iteration methods in Hilbert scales. % By exploiting…

Numerical Analysis · Mathematics 2015-05-20 Qinian Jin , Ulrich Tautenhahn

Although it is relatively easy to apply, the gradient method often displays a disappointingly slow rate of convergence. Its convergence is specially based on the structure of the matrix of the algebraic linear system, and on the choice of…

Numerical Analysis · Mathematics 2025-06-03 Ibrahima Dione

In this paper we address the numerical solution of nonlinear ill-posed systems by iterative regularization methods in the classes of Levenberg-Marquardt, trust-region and adaptive quadratic regularization procedures. Both with exact and…

Numerical Analysis · Mathematics 2015-04-17 Stefania Bellavia , Benedetta Morini

In the present work, a simple algorithm for stabilizing an unknown linear time-invariant system is proposed, assuming only that this system is stabilizable. The suggested algorithm is based on first performing a partial identification of…

Optimization and Control · Mathematics 2022-11-14 Dennis Gramlich , Christian Ebenbauer

This work connects two mathematical fields - computational complexity and interval linear algebra. It introduces the basic topics of interval linear algebra - regularity and singularity, full column rank, solving a linear system, deciding…

Computational Complexity · Computer Science 2016-02-02 Jaroslav Horáček , Milan Hladík , Michal Černý

We investigate implicit regularization schemes for gradient descent methods applied to unpenalized least squares regression to solve the problem of reconstructing a sparse signal from an underdetermined system of linear measurements under…

Machine Learning · Statistics 2019-09-12 Tomas Vaškevičius , Varun Kanade , Patrick Rebeschini

Consider using the right-preconditioned GMRES (AB-GMRES) for obtaining the minimum-norm solution of inconsistent underdetermined systems of linear equations. Morikuni (Ph.D. thesis, 2013) showed that for some inconsistent and…

Numerical Analysis · Mathematics 2022-05-25 Zeyu Liao , Ken Hayami , Keiichi Morikuni , Jun-Feng Yin

In this note we construct a solution of a matrix interval linear equation of the form X=AX+B (the discrete stationary Bellman equation) over partially ordered semirings, including the semiring of nonnegative real numbers and all idempotent…

Rings and Algebras · Mathematics 2007-05-23 Grigori Litvinov , Andrei Sobolevskii

In this article we develop and analyze novel iterative regularization techniques for the solution of systems of nonlinear ill--posed operator equations. The basic idea consists in considering separately each equation of this system and…

Numerical Analysis · Mathematics 2020-11-20 M. Haltmeier , A. Leitao , O. Scherzer

Interior-point methods for linear programming problems require the repeated solution of a linear system of equations. Solving these linear systems is non-trivial due to the severe ill-conditioning of the matrices towards convergence. This…

Optimization and Control · Mathematics 2021-05-05 Jeffrey Cornelis , Wim Vanroose
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