Computational Linear Algebra (Hardcover)

Robert E. White

ISBN 10: 1032302461 / ISBN 13: 9781032302461

Edité par Taylor & Francis Ltd, London, 2023

A propos de cet article

Hardcover. 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. The general inner product vector spaces are considered starting in the middle of the text.The text has a number of applications. These are to motivate the student to study the linear algebra topics. Also, the text has a number of computations. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032302461

Détails bibliographiques

Titre : Computational Linear Algebra (Hardcover)

Éditeur : Taylor & Francis Ltd, London

Date d'édition : 2023

Reliure : Hardcover

Etat : new

A propos de ce titre

Synopsis :

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. The general inner product vector spaces are considered starting in the middle of the text.

The text has a number of applications. These are to motivate the student to study the linear algebra topics. Also, the text has a number of computations. MATLAB(R) 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.

À propos de l?auteur:

Robert E. White is Professor Emeritus, North Carolina State University. He is also the author of Computational Mathematics: Models, Methods, Analysis with MATLAB(R) and MPI, second edition and Elements of Matrix Modeling and Computing with MATLAB(R), both published by CRC Press.