Introduction to Linear Algebra
Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains all the qualities of earlier editions, while at the same time seeing numerous minor improvements and major additions. The latter include:
• A new chapter on singular values and singular vectors, including ways to analyze a matrix of data
• A revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages
• A new section on linear algebra and cryptography
• A new chapter on linear algebra in probability and statistics.
A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (including practice problems, exams, and development of textbook examples), plus codes in MATLAB®, Julia, and Python.
- This fifth edition contains numerous minor improvements and major additions
- Provides a new chapter on singular values and singular vectors, as well as a revised chapter on computing in linear algebra
- A dedicated and active website offers solutions to exercises, new exercises from several sources, and codes in MATLAB®, Julia, and Python
Reviews & endorsements
'Undergraduate mathematics textbooks are not what they used to be, and Gilbert Strang's superb new edition of Introduction to Linear Algebra is an example of everything that a modern textbook could possibly be, and more … the writing is engaging and personal, and the presentation is exceptionally clear and informative (even seasoned instructors may benefit from Strang's insights) … I would like to stress that there is a richness to the material that goes beyond most texts at this level.' Douglas Farenick, Bulletin of the International Linear Algebra Society
Product details
August 2016Hardback
9780980232776
600 pages
237 × 198 × 31 mm
1.17kg
Out of stock in print form with no current plan to reprint
Table of Contents
- 1. Introduction to vectors
- 2. Solving linear equations
- 3. Vector spaces and subspaces
- 4. Orthogonality
- 5. Determinants
- 6. Eigenvalues and eigenvectors
- 7. The singular value decomposition (SVD)
- 8. Linear transformations
- 9. Complex vectors and matrices
- 10. Applications
- 11. Numerical linear algebra
- 12. Linear algebra in probability and statistics
- Matrix factorizations
- Index
- Six great theorems/linear algebra in a nutshell.