Matrix Analysis for Scientists and Engineers
Matrix Analysis for Scientists and Engineers provides a blend of undergraduate- and graduate-level topics in matrix theory and linear algebra that relieves instructors of the burden of reviewing such material in subsequent courses that depend heavily on the language of matrices. Consequently, the text provides an often-needed bridge between undergraduate-level matrix theory and linear algebra and the level of matrix analysis required for graduate-level study and research. The text is sufficiently compact that the material can be taught comfortably in a one-quarter or one-semester course. Throughout the book, the author emphasizes the concept of matrix factorization to provide a foundation for a later course in numerical linear algebra. The author addresses connections to differential and difference equations as well as to linear system theory and encourages instructors to augment these examples with other applications of their own choosing.
- Primarily intended to be used as a text for senior undergraduate or beginning graduate students in engineering, the sciences, mathematics, computer science, or computational science
- Also useful for individual engineers and scientists who need a concise reference or a text for self-study; a knowledge of calculus and some previous exposure to matrices and linear algebra are required
- Exercises are provided at the end of each chapter
Reviews & endorsements
'I found Laub's book a delightful read. It has become the sixth valuable 'Matrix Analysis' book on my shelves. As well as being admirably suited for the course at which it is aimed, its conciseness and clarity of presentation, together with the good index, make it easy to use for reference. The book is recommended both as a course text and as a handy guide to the subject.' Nicholas J. Higham, SIAM Review
Product details
December 2004Paperback
9780898715767
184 pages
255 × 178 × 9 mm
0.326kg
This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
- Preface
- 1. Introduction and review
- 2. Vector spaces
- 3. Linear transformations
- 4. Introduction to the Moore-Penrose pseudoinverse
- 5. Introduction to the singular value decomposition
- 6. Linear equations
- 7. Projections, inner product spaces, and norms
- 8. Linear least squares problems
- 9. Eigenvalues and eigenvectors
- 10. Canonical forms
- 11. Linear differential and difference equations
- 12. Generalized eigenvalue problems
- 13. Kronecker products
- Bibliography
- Index.