Studies on Numerical Linear Algebra with Symmetry/Asymmetry
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 123
Special Issue Editors
Interests: numerical analysis
Interests: ill-posed and inverse problems, iterative methods for large linear systems of equations; structured problems in linear algebra, Krylov subspace methods
Special Issue Information
Dear Colleagues,
Numerical linear algebra focuses on using matrix operations to produce computer algorithms for efficient computation of approximate solutions to continuous mathematics, using finite precision computers. It is often a fundamental part of engineering and computational science problems, such as image and signal processing and telecommunication. Common problems in numerical linear algebra include computing matrix decompositions, such as computing its eigenvalues and eigenvectors, singular-value decomposition, QR, or LU factorization.
Dr. Dušan Lj Djukić
Prof. Dr. Lothar Reichel
Prof. Carlos F. Borges
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- numerical analysis
- linear algebra
- matrix decomposition
- eigendecomposition
- iterative methods
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