AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (988.6 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

A partially block randomized extended Kaczmarz method for solving large overdetermined inconsistent linear systems

Feng Yin1,3( )Bu-Yue Zhang1,3Guang-Xin Huang2,3
College of Mathematical and Physics, Chengdu University of Technology, Chengdu 610059, China
College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu 610059, China
Sichuan Geomathematics Key Laboratory, Chengdu University of Technology, Chengdu 610059, China
Show Author Information

Abstract

This paper presents a partial block randomized extended Kaczmarz (PBREK) method for solving large overdetermined inconsistent linear system of equations A x = b. The convergence theorem of the PBREK method is derived. Several examples are given to illustrate the effectiveness of the proposed PBREK method compared with the prevuious PREK method and the randomized extended Kaczmarz (REK) method.

CLC number: 65F10, 65F20

References

【1】
【1】
 
 
AIMS Mathematics
Pages 18512-18527

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Yin F, Zhang B-Y, Huang G-X. A partially block randomized extended Kaczmarz method for solving large overdetermined inconsistent linear systems. AIMS Mathematics, 2023, 8(8): 18512-18527. https://doi.org/10.3934/math.2023941

10

Views

0

Downloads

2

Crossref

2

Web of Science

2

Scopus

Received: 22 December 2022
Revised: 08 May 2023
Accepted: 15 May 2023
Published: 15 August 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)