/AppliedLinear

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MATH 307 Applied Linear Algebra

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