Numerical linear algebra / Folkmar Bornemann. a concise introduction with MATLAB and Julia.
By: Bornemann, Folkmar [author.].
Contributor(s): Simson, Walter [translator.].
Material type: TextSeries: Springer Undergraduate Mathematics Series.Publisher: New York, NY : Springer Berlin Heidelberg, 2018Description: x, 153 pages; E 44.99 23 cms.Content type: text Media type: unmediated Carrier type: volumeISBN: 9783319742212 (alk. paper).Subject(s): Algebras, Linear | Numerical calculationsSummary: This book offers an introduction to the algorithmic-numerical thinking using basic problems of linear algebra. By focusing on linear algebra, it ensures a stronger thematic coherence than is otherwise found in introductory lectures on numerics. The book highlights the usefulness of matrix partitioning compared to a component view, leading not only to a clearer notation and shorter algorithms, but also to significant runtime gains in modern computer architectures. The algorithms and accompanying numerical examples are given in the programming environment MATLAB, and additionally – in an appendix – in the future-oriented, freely accessible programming language Julia. This book is suitable for a two-hour lecture on numerical linear algebra from the second semester of a bachelor's degree in mathematics.Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Book | Chennai Mathematical Institute General Stacks | 512.5 BOR (Browse shelf) | Available | 10637 |
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512.482 STI Naive lie theory / | 512.482 TAP Matrix groups for undergraduates / | 512.5 ANT Elementary linear algebra with applications / | 512.5 BOR Numerical linear algebra / a concise introduction with MATLAB and Julia. | 512.5 COL Dynamical systems and linear algebra / | 512.5 CUR Linear algebra : an introductory approach / | 512.5 DEE Interactive linear algebra with Maple V / |
This book offers an introduction to the algorithmic-numerical thinking using basic problems of linear algebra. By focusing on linear algebra, it ensures a stronger thematic coherence than is otherwise found in introductory lectures on numerics. The book highlights the usefulness of matrix partitioning compared to a component view, leading not only to a clearer notation and shorter algorithms, but also to significant runtime gains in modern computer architectures. The algorithms and accompanying numerical examples are given in the programming environment MATLAB, and additionally – in an appendix – in the future-oriented, freely accessible programming language Julia. This book is suitable for a two-hour lecture on numerical linear algebra from the second semester of a bachelor's degree in mathematics.