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Название: Computational Linear Algebra: with Applications and MATLAB Computations
Автор: Robert E. White
Издательство: CRC Press
Год: 2023
Страниц: 330
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
Courses on linear algebra and numerical analysis need each other. Often NA courses have some linear algebra topics, and LA courses mention some topics from numerical analysis/scientific computing. This text merges these two areas into one introductory undergraduate course. It assumes students have had multivariable calculus. A second goal of this text is to demonstrate the intimate relationship of linear algebra to applications/computations. A rigorous presentation has been maintained. A third reason for writing this text is to present, in the first half of the course, the very important topic on singular value decomposition, SVD. This is done by first restricting consideration to real matrices and vector spaces. MATLAB is used, but one could modify these codes to other programming languages. These are either to simplify some linear algebra computation, or to model a particular application.
Автор: Robert E. White
Издательство: CRC Press
Год: 2023
Страниц: 330
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
Courses on linear algebra and numerical analysis need each other. Often NA courses have some linear algebra topics, and LA courses mention some topics from numerical analysis/scientific computing. This text merges these two areas into one introductory undergraduate course. It assumes students have had multivariable calculus. A second goal of this text is to demonstrate the intimate relationship of linear algebra to applications/computations. A rigorous presentation has been maintained. A third reason for writing this text is to present, in the first half of the course, the very important topic on singular value decomposition, SVD. This is done by first restricting consideration to real matrices and vector spaces. MATLAB is used, but one could modify these codes to other programming languages. These are either to simplify some linear algebra computation, or to model a particular application.