MATH 307 is an introduction to applied linear algebra including:
- Linear systems of equations: LU and Cholesky decompositions and conditioning
- Least squares approximation: normal equations, QR decomposition and orthogonalization
- Eigenvalue problems: spectral theorem, singular value decomposition and eigenvalue algorithms
- Digital signal processing: discrete Fourier transform, fast Fourier transform and the convolution theorem
- Applications: interpolation, finite difference method, data fitting, computed tomography, image processing, signal processing, network analysis, PageRank and more
| Notebook | Topics |
|---|---|
| 01_linear_systems | Linear systems of equations |
| 02_LU_decomposition | LU decomposition |
| 03_polynomial_interpolation | Polynomial interpolation |
| 04_spline_interpolation | Cubic spline interpolation |
| 05_finite_difference_method | Finite difference method |
| 06_least_squares_regression | Least squares regression |
| 07_computed_tomography | Computed tomography |
| 08_computing_eigenvalues | Computing eigenvalues |
| 09_pca | Principal component analysis |
| 10_deblurring_images | Deblurring images |
| 11_pagerank | PageRank |