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Numerical Linear Algebra: Theory and Applications
| Beilina, Larisa;Karchevskii, Mikhail;Karchevskii, Evgenii
Hardcover
2018 Springer International Publishing
Auflage: 04.07.2017 Auflage
XIV, 450 Seiten; XIV, 450 p. 15 illus., 14 illus. in color. With online files/update.; 23.5 cm x 15.5 cm
Sprache: English
ISBN: 978-3-319-57302-1
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Inhalt
Autorentext: 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. Inhalt: 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 extensively 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 in the Appendix 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. Zusatztext: 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 extensively 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 in the Appendix 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.
Autorentext: 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. Inhalt: 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 extensively 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 in the Appendix 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. Zusatztext: 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 extensively 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 in the Appendix 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.