
Linear Algebra with Applications
United States Edition
Otto Bretscher(Author)
Pearson (Publisher)
2nd Edition
Published on 6. March 2001
Book
Hardback
440 pages
978-0-13-019857-0 (ISBN)
Article exhausted; check for reprint
Description
For courses in Introductory Linear Algebra and Matrix Methods.
With the most geometric presentation now available, this text emphasizes linear transformations as a unifying theme, and enables students to "do" both computational and abstract math in each chapter. A second theme is introduced half way through the text-when eigenvectors are reached-on dynamical systems. It also includes a wider range of problem sets than found in any other text in this market.
With the most geometric presentation now available, this text emphasizes linear transformations as a unifying theme, and enables students to "do" both computational and abstract math in each chapter. A second theme is introduced half way through the text-when eigenvectors are reached-on dynamical systems. It also includes a wider range of problem sets than found in any other text in this market.
More details
Edition
2nd edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 241 mm
Width: 210 mm
Thickness: 25 mm
Weight
1012 gr
ISBN-13
978-0-13-019857-0 (9780130198570)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Book
07/2004
3rd Edition
Pearson
€100.27
Article exhausted; check for reprint
Previous edition
Otto Bretscher
Linear Algebra with Applications
Book
01/1997
Pearson
€42.08
Article exhausted; check for reprint
Content
1. Systems of Linear Equations.
2. Linear Transformations.
3. Subspaces of Rn and Their Dimension.
4. Linear Spaces.
5. Orthogonality and Least Squares.
6. Determinants.
7. Eigenvalues and Eigenvectors.
8. Symmetric Matrices and Quadratic Forms.
9. Linear Differential Equations.
2. Linear Transformations.
3. Subspaces of Rn and Their Dimension.
4. Linear Spaces.
5. Orthogonality and Least Squares.
6. Determinants.
7. Eigenvalues and Eigenvectors.
8. Symmetric Matrices and Quadratic Forms.
9. Linear Differential Equations.