Numerical Linear Algebra: Theory and Applications

Nonfiction, Science & Nature, Mathematics, Algebra
Cover of the book Numerical Linear Algebra: Theory and Applications by Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii, Springer International Publishing
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Author: Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii ISBN: 9783319573045
Publisher: Springer International Publishing Publication: September 19, 2017
Imprint: Springer Language: English
Author: Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
ISBN: 9783319573045
Publisher: Springer International Publishing
Publication: September 19, 2017
Imprint: Springer
Language: English

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a number of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear systems of equations, spectral theory, vector and matrix norms combined with main direct and iterative numerical methods, least squares problems, and eigenproblems. Numerical algorithms illustrated by computer programs written in MATLAB® are also provided as supplementary material on SpringerLink to give the reader a better understanding of professional numerical software for the solution of real-life problems. Perfect for a one- or two-semester course on numerical linear algebra, matrix computation, and large sparse matrices, this text will interest students at the advanced undergraduate or graduate level.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a number of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear systems of equations, spectral theory, vector and matrix norms combined with main direct and iterative numerical methods, least squares problems, and eigenproblems. Numerical algorithms illustrated by computer programs written in MATLAB® are also provided as supplementary material on SpringerLink to give the reader a better understanding of professional numerical software for the solution of real-life problems. Perfect for a one- or two-semester course on numerical linear algebra, matrix computation, and large sparse matrices, this text will interest students at the advanced undergraduate or graduate level.

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