An innovative algorithm for estimating the minimum eigenvalue of M-matrices

Abstract For a general M-matrix, we construct a specialized matrix to derive monotonically increasing lower bounds and monotonically decreasing upper bounds for its minimum eigenvalue. These results generalize and significantly improve upon existing related findings. Furthermore, we rigorously prove...

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Main Authors: Qin Zhong, Ling Li, Gufang Mou
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Journal of Inequalities and Applications
Subjects:
Online Access:https://doi.org/10.1186/s13660-025-03335-1
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author Qin Zhong
Ling Li
Gufang Mou
author_facet Qin Zhong
Ling Li
Gufang Mou
author_sort Qin Zhong
collection DOAJ
description Abstract For a general M-matrix, we construct a specialized matrix to derive monotonically increasing lower bounds and monotonically decreasing upper bounds for its minimum eigenvalue. These results generalize and significantly improve upon existing related findings. Furthermore, we rigorously prove the monotonicity and convergence properties of these bounds. Finally, for a non-defective M-matrix, we propose a smoothing algorithm to compute its minimum eigenvalue, and we validate the effectiveness of the algorithm through numerical examples.
format Article
id doaj-art-720fa5efb5d745d19a608b11685df3b7
institution DOAJ
issn 1029-242X
language English
publishDate 2025-07-01
publisher SpringerOpen
record_format Article
series Journal of Inequalities and Applications
spelling doaj-art-720fa5efb5d745d19a608b11685df3b72025-08-20T03:06:39ZengSpringerOpenJournal of Inequalities and Applications1029-242X2025-07-012025111410.1186/s13660-025-03335-1An innovative algorithm for estimating the minimum eigenvalue of M-matricesQin Zhong0Ling Li1Gufang Mou2Department of Mathematics, Sichuan University Jinjiang CollegeSchool of Big Data and Artificial Intelligence, Chengdu Technological UniversityCollege of Applied Mathematics, Chengdu University of Information TechnologyAbstract For a general M-matrix, we construct a specialized matrix to derive monotonically increasing lower bounds and monotonically decreasing upper bounds for its minimum eigenvalue. These results generalize and significantly improve upon existing related findings. Furthermore, we rigorously prove the monotonicity and convergence properties of these bounds. Finally, for a non-defective M-matrix, we propose a smoothing algorithm to compute its minimum eigenvalue, and we validate the effectiveness of the algorithm through numerical examples.https://doi.org/10.1186/s13660-025-03335-1M-matrixMinimum eigenvalueUpper boundLower boundNon-defective matrix
spellingShingle Qin Zhong
Ling Li
Gufang Mou
An innovative algorithm for estimating the minimum eigenvalue of M-matrices
Journal of Inequalities and Applications
M-matrix
Minimum eigenvalue
Upper bound
Lower bound
Non-defective matrix
title An innovative algorithm for estimating the minimum eigenvalue of M-matrices
title_full An innovative algorithm for estimating the minimum eigenvalue of M-matrices
title_fullStr An innovative algorithm for estimating the minimum eigenvalue of M-matrices
title_full_unstemmed An innovative algorithm for estimating the minimum eigenvalue of M-matrices
title_short An innovative algorithm for estimating the minimum eigenvalue of M-matrices
title_sort innovative algorithm for estimating the minimum eigenvalue of m matrices
topic M-matrix
Minimum eigenvalue
Upper bound
Lower bound
Non-defective matrix
url https://doi.org/10.1186/s13660-025-03335-1
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AT gufangmou aninnovativealgorithmforestimatingtheminimumeigenvalueofmmatrices
AT qinzhong innovativealgorithmforestimatingtheminimumeigenvalueofmmatrices
AT lingli innovativealgorithmforestimatingtheminimumeigenvalueofmmatrices
AT gufangmou innovativealgorithmforestimatingtheminimumeigenvalueofmmatrices