Overview
- Authors:
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Larisa Beilina
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Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
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Evgenii Karchevskii
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Department of Applied Mathematics, Kazan Federal University, Kazan, Tatarstan Republic, Russia
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Mikhail Karchevskii
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Department of Computational Mathematics, Kazan Federal University, Kazan, Tatarstan Republic, Russia
Presents extended basic theory of linear algebra
Includes programs in MATLAB that provide students with experience in implementation and evaluation of numerical algorithms
Perfect for a one or two semester course at the advanced undergraduate or graduate level
Includes supplementary material: sn.pub/extras
Includes supplementary material: sn.pub/extras
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Table of contents (13 chapters)
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 1-54
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 55-68
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 69-92
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 93-162
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 163-208
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 209-229
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 231-248
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 249-289
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 291-343
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 345-374
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 375-405
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages 407-439
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- Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii
Pages E1-E1
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Back Matter
Pages 441-450
About this book
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.
Reviews
“It provides a rock-solid theoretical background in a very approachable manner, a good overview of classical algorithms of numerical linear algebra and a good framework and guidance for numerical experiments.” (Cyril Fischer, zbMATH 1396.65001, 2018)
Authors and Affiliations
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Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
Larisa Beilina
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Department of Applied Mathematics, Kazan Federal University, Kazan, Tatarstan Republic, Russia
Evgenii Karchevskii
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Department of Computational Mathematics, Kazan Federal University, Kazan, Tatarstan Republic, Russia
Mikhail Karchevskii
About the authors
Larisa Beilina is an Associate Professor in the Department of Mathematical Sciences at Chalmers University of Technology and Gothenburg University.
Evgenii Karchevskii and Mikhail Karchevskii are both professors at the Institute of Computer Mathematics and Information Technologies at Kazan Federal University, Russia.
