Sale 13%
Springer
Linear Algebra
Product Code:
9789811309250
ISBN13:
9789811309250
Condition:
New
$71.00
This book introduces the fundamental concepts, techniques and results of linear algebra that form the basis of analysis, applied mathematics and algebra. Intended as a text for undergraduate students of mathematics, science and engineering with a knowledge of set theory, it discusses the concepts that are constantly used by scientists and engineers. It also lays the foundation for the language and framework for modern analysis and its applications. Divided into seven chapters, it discusses vector spaces, linear transformations, best approximation in inner product spaces, eigenvalues and eigenvectors, block diagonalisation, triangularisation, Jordan form, singular value decomposition, polar decomposition, and many more topics that are relevant to applications. The topics chosen have become well-established over the years and are still very much in use. The approach is both geometric and algebraic. It avoids distraction from the main theme by deferring the exercises to the end of each section. These exercises aim at reinforcing the learned concepts rather than as exposing readers to the tricks involved in the computation. Problems included at the end of each chapter are relatively advanced and require a deep understanding and assimilation of the topics.
| Author: M. Thamban Nair, Arindama Singh |
| Publisher: Springer |
| Publication Date: Aug 02, 2018 |
| Number of Pages: 341 pages |
| Language: English |
| Binding: Hardcover |
| ISBN-10: 9811309256 |
| ISBN-13: 9789811309250 |
Linear Algebra
$71.00
This book introduces the fundamental concepts, techniques and results of linear algebra that form the basis of analysis, applied mathematics and algebra. Intended as a text for undergraduate students of mathematics, science and engineering with a knowledge of set theory, it discusses the concepts that are constantly used by scientists and engineers. It also lays the foundation for the language and framework for modern analysis and its applications. Divided into seven chapters, it discusses vector spaces, linear transformations, best approximation in inner product spaces, eigenvalues and eigenvectors, block diagonalisation, triangularisation, Jordan form, singular value decomposition, polar decomposition, and many more topics that are relevant to applications. The topics chosen have become well-established over the years and are still very much in use. The approach is both geometric and algebraic. It avoids distraction from the main theme by deferring the exercises to the end of each section. These exercises aim at reinforcing the learned concepts rather than as exposing readers to the tricks involved in the computation. Problems included at the end of each chapter are relatively advanced and require a deep understanding and assimilation of the topics.
| Author: M. Thamban Nair, Arindama Singh |
| Publisher: Springer |
| Publication Date: Aug 02, 2018 |
| Number of Pages: 341 pages |
| Language: English |
| Binding: Hardcover |
| ISBN-10: 9811309256 |
| ISBN-13: 9789811309250 |
Related Products
Sale 4%
