MATH 3NA3
NUMERICAL LINEAR ALGEBRA
Fall 2026 · C01
Topics
- MATLAB basics
- Matrices and vectors
- Floating-point arithmetic
- Accuracy, efficiency, and robustness
- Operation counts and computational complexity
- Vector and matrix norms
- Conditioning and error analysis
- LU factorization
- Cholesky factorization
- Jacobi and Gauss-Seidel iterative methods
- Convergence of iterative methods
- Bisection method
- Fixed-point iteration
- Newton's method
- Systems of nonlinear equations
- Symmetric and orthogonal matrices
- Orthogonal projections
- QR factorization
- Least-squares problems and data fitting
- Basic properties of eigenvalues and eigenvectors
- Power iteration
- Rayleigh quotient iteration
- Deflation and QR iteration
- Singular value decomposition
- Sensitivity of eigenvalue problems
Readings
- Numerical Mathematics
- MATLAB
- Numerical Linear AlgebraSpringer · ISBN 978-0-387-68918-0
- Numerical Linear Algebra ISBN: 978-0-387-68918-0 Authors: Grégoire Allaire and Sidi Mahmoud Kaber Publisher: Springer Publication Date: 2008 This is a supplementary reference for the course. An electronic version is available through the McMaster University Library.
Sources
- Course catalogue ↗2026–2027
- Campus Store (short title) ↗
- Campus Store reading list ↗Fall 2025
- Course outline / syllabus ↗Fall 2026
- Numerical Mathematics Authors: Mattheus R. Grasselli and Dmitry E. Pelinovsky Edition: 2nd The textbook will be available in PDF format free of charge through Avenue to Learn.