- Pràctica 1: C++. LU Decomposition and main operations of matrices
- LU Decomposition.
- Gauss and resolution (Doolittle method).
- 1,2,inf vectorial norms of the error yielded when calculating the solution.
- 1,2,inf matricial norms of the error yielded when decomposing the matrix A.
- Calculation of the inverse matrix.
- Calculation of the transposed matrix.
- Calculation of the determinant of the matrix A.
- Calculation of the S= A^{T} * A symmetric matrix.
- Calculation of the eigenvalues of any matrix.
- Pràctica 2:MATLAB. Approximation by least squares. Quadratic model.
- QR Decomposition.
- Overdeterminate system resolution.
- Eigenvalues and eigenvectors calculation without the eig() function.
- Error yielded when calculating the solution.
3.Pràctica 3: MATLAB. Main iterative methods.
- Jacobi method.
- Gauss-Seidel method.
- OverRelaxation method.
4.Pràctica 4: MATLAB. Power Methods / Eigenvalues
- Mètode de la potència
- Mètode de la potència inversa. INVERSE
- Mètode de la potència desplaçada. TRANSLATED.
- Mètode de la potència inversa desplaçada. INVERSE AND TRANSLATED. (we could also use LU to solve A(z_{k+1}) = z_{k})