| Code |
Course Name |
Language |
Type |
| MAT 263E |
Computational Linear Algebra |
English |
Compulsory |
| Local Credits |
ECTS |
Theoretical |
Tutorial |
Laboratory |
| 3 |
7 |
3 |
0 |
0 |
| Course Prerequisites and Class Restriction |
| Prerequisites |
MAT 143 MIN DD
or MAT 143E MIN DD
or MAT 141 MIN DD
or MAT 141E MIN DD
or EEE 281E MIN DD
or EEF 281 MIN DD
or EEF 281E MIN DD
or END 210 MIN DD
or END 210E MIN DD
or IND 210E MIN DD
or MAK 114 MIN DD
or MAT 261 MIN DD
or MAT 261E MIN DD
or MAT 262E MIN DD
or MAT 281 MIN DD
or MAT 281E MIN DD
or MTH 204 MIN DD
or MAT 210 MIN DD
or MAT 210E MIN DD
or CEV 210 MIN DD
or CEV 210E MIN DD
or DEN 210E MIN DD
or FIZ 210 MIN DD
or GEM 210E MIN DD
|
| Class Restriction |
None |
| Course Description |
| The concepts of vector and matrix norms, positive definite matrix, linear independence, dimensions and bases. Solution of linear
systems: Direct methods (Gauss-Elimination, Gauss-Jordan, pivoting, Cramer methods, LU, Cholesky and QR decompositions),
Iterative methods (Jacobi and Gauss-Seidel 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 eigenvalue-
eigenvector problems with popular programming languages. Singular value decomposition. |
|
