MAT 263  Computational Linear Algebra
Course Objectives
1. To learn numerical solutions of linear systems,
2. To solve numerically eigenvalueeigenvector problems,
3. To analyze convergence of iterative methods,
4. To solve linear algebra problems with popular programming languages,
Course Description
The concepts of vector and matrix norms, positive definite matrix, linear independence, dimensions and bases. Solution of linear systems: Direct methods (GaussElimination, GaussJordan, pivoting, Cramer methods, LU, Cholesky and QR decompositions), Iterative methods (Jacobi and GaussSeidel methods, Successive over relaxation method) and convergence analysis, Solutions of linear systems with popular programming languages. Eigenvalue and eigenvector problems: Gerschgorin disks, Rayleigh quotient, Trace method, Power and inverse power methods and power method with shifting. Solutions of eigenvalueeigenvector problems with popular programming languages. Singular value decomposition.


Course Coordinator
Ersin Özuğurlu
Course Language
English


