Two Iterative Methods for Solving Linear Interval Systems

Conjugate gradient is an iterative method that solves a linear system Ax=b, where A is a positive definite matrix. We present this new iterative method for solving linear interval systems Ãx̃=b̃, where à is a diagonally dominant interval matrix, as defined in this paper. Our method is based on con...

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Main Authors: Esmaeil Siahlooei, Seyed Abolfazl Shahzadeh Fazeli
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/2018/2797038
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spelling doaj-6555a0417a374f5b8a8541ebae10d0fb2020-11-25T00:52:59ZengHindawi LimitedApplied Computational Intelligence and Soft Computing1687-97241687-97322018-01-01201810.1155/2018/27970382797038Two Iterative Methods for Solving Linear Interval SystemsEsmaeil Siahlooei0Seyed Abolfazl Shahzadeh Fazeli1Department of Computer Science, Yazd University, Yazd, IranDepartment of Computer Science, Yazd University, Yazd, IranConjugate gradient is an iterative method that solves a linear system Ax=b, where A is a positive definite matrix. We present this new iterative method for solving linear interval systems Ãx̃=b̃, where à is a diagonally dominant interval matrix, as defined in this paper. Our method is based on conjugate gradient algorithm in the context view of interval numbers. Numerical experiments show that the new interval modified conjugate gradient method minimizes the norm of the difference of Ãx̃ and b̃ at every step while the norm is sufficiently small. In addition, we present another iterative method that solves Ãx̃=b̃, where à is a diagonally dominant interval matrix. This method, using the idea of steepest descent, finds exact solution x̃ for linear interval systems, where Ãx̃=b̃; we present a proof that indicates that this iterative method is convergent. Also, our numerical experiments illustrate the efficiency of the proposed methods.http://dx.doi.org/10.1155/2018/2797038
collection DOAJ
language English
format Article
sources DOAJ
author Esmaeil Siahlooei
Seyed Abolfazl Shahzadeh Fazeli
spellingShingle Esmaeil Siahlooei
Seyed Abolfazl Shahzadeh Fazeli
Two Iterative Methods for Solving Linear Interval Systems
Applied Computational Intelligence and Soft Computing
author_facet Esmaeil Siahlooei
Seyed Abolfazl Shahzadeh Fazeli
author_sort Esmaeil Siahlooei
title Two Iterative Methods for Solving Linear Interval Systems
title_short Two Iterative Methods for Solving Linear Interval Systems
title_full Two Iterative Methods for Solving Linear Interval Systems
title_fullStr Two Iterative Methods for Solving Linear Interval Systems
title_full_unstemmed Two Iterative Methods for Solving Linear Interval Systems
title_sort two iterative methods for solving linear interval systems
publisher Hindawi Limited
series Applied Computational Intelligence and Soft Computing
issn 1687-9724
1687-9732
publishDate 2018-01-01
description Conjugate gradient is an iterative method that solves a linear system Ax=b, where A is a positive definite matrix. We present this new iterative method for solving linear interval systems Ãx̃=b̃, where à is a diagonally dominant interval matrix, as defined in this paper. Our method is based on conjugate gradient algorithm in the context view of interval numbers. Numerical experiments show that the new interval modified conjugate gradient method minimizes the norm of the difference of Ãx̃ and b̃ at every step while the norm is sufficiently small. In addition, we present another iterative method that solves Ãx̃=b̃, where à is a diagonally dominant interval matrix. This method, using the idea of steepest descent, finds exact solution x̃ for linear interval systems, where Ãx̃=b̃; we present a proof that indicates that this iterative method is convergent. Also, our numerical experiments illustrate the efficiency of the proposed methods.
url http://dx.doi.org/10.1155/2018/2797038
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AT seyedabolfazlshahzadehfazeli twoiterativemethodsforsolvinglinearintervalsystems
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