MATH 4366 - Numerical Linear Algebra
***This is a course guideline. Students should contact instructor for the updated information on current course syllabus, textbooks, and course content***
Prerequisites: MATH 2318, or equivalent, and six additional hours of 3000—4000 level Mathematics.
Course Description: Conditioning and stability of linear systems, matrix factorizations, direct and iterative methods for solving linear systems, computing eigenvalues and eigenvectors, introduction to linear and nonlinear optimization.
Textbooks:
- Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares, by S. Boyd (Stanford) and L. Vandenberghe (UCLA). ISBN: 978-1316518960.
- Matrix Factorizations, Iterative Methods, Minimization, a class note by L. Vandenberghe (UCLA).
Course Content:
Conditioning and stability of linear systems, matrix factorizations, direct and iter- ative methods for solving linear systems, computing eigenvalues and eigenvectors, introduction to linear and nonlinear optimization.
- Introduction; Vectors
- Norm, distance, angle
- Matrices
- Matrix inverses
- Orthogonal matrices
- QR factorization
- Linear equations
- Least squares
- Least squares applications
- Multi-objective least squares
- Constrained least squares
- Cholesky factorization
- Nonlinear least squares
Course Structure and Grading Policies: Please consult your instructor's syllabus regarding any and all grading/course structure guidelines.
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