Numerical Linear Algebra with Applications
Using MATLAB and Octave
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Product details:
- Edition number 2
- Publisher Academic Press
- Date of Publication 10 June 2025
- ISBN 9780443134760
- Binding Paperback
- No. of pages678 pages
- Size 276x216 mm
- Weight 450 g
- Language English 700
Categories
Long description:
Numerical Linear Algebra with Applications: Using MATLAB and Octave, Second Edition provides practical knowledge on modern computational techniques for the numerical solution of linear algebra problems. The book offers a unified presentation of computation, basic algorithm analysis, and numerical methods to compute solutions. Useful to readers regardless of background, the text begins with six introductory courses to provide background for those who haven’t taken applied or theoretical linear algebra. This approach offers a thorough explanation of the issues and methods for practical computing using MATLAB as the vehicle for computation.
Appropriate for advanced undergraduate and early graduate courses on numerical linear algebra, this useful textbook explores numerous applications to engineering and science.
- Features six introductory chapters to provide the required background for readers without coursework in applied or theoretical linear algebra
- Offers a through discussion of the algorithms necessary for the accurate computation of the solution to the most frequently occurring problems in numerical linear algebra
- Provides illustrative examples from engineering and science applications
- Includes online teaching support for qualified instructors (Solutions Manual, PowerPoint Slides) and study materials for students (Text examples, Algorithms)
Table of Contents:
1. Matrices
2. Linear equations
3. Subspaces
4. Determinants
5. Eigenvalues and eigenvectors
6. Orthogonal vectors and matrices
7. Vector and matrix norms
8. Floating point arithmetic
9. Algorithms
10. Conditioning of problems and stability of algorithms
11. Gaussian elimination and the LU decomposition
12. Linear system applications
13. Important special systems
14. Gram-Schmidt decomposition
15. The singular value decomposition
16. Least-squares problems
17. Implementing the QR factorization
18. The algebraic eigenvalue problem
19. The symmetric eigenvalue problem
20. Basic iterative methods
21. Krylov subspace methods
22. Large sparse eigenvalue problems
23. Computing the singular value decomposition
