"Notes on Computational Mathematics", (by Robert Higdon).
Various course materials:
- Linear algebra (MTH 351, 451, 551)
- Conjugate Gradient Method:
mycgs.m
(by M. Peszynska)
- Conjugate Gradient versus Steepest Descent 3D demo: cgdemo.m (by D. Fettig)
- Preconditioned Conjugate Gradient Method:
mypcg.m
(by M. Peszynska)
- Demo of how the use of preconditioners affects the spectral properties of a matrix and the number of iterations in PCG: pcgdemo.m (by D. Fettig, M. Peszynska)
-
SVD (Singular Value Decomposition) demo of application to image processing:
svd_demo.m
(by M. Peszynska)
- SVD (Singular Value Decomposition) demo ... actual image: svd_demo_with_image.m (by J. Kyle)
- sample BMP image arcdbk.bmp (by J. Kyle)
-
Gram_Schmidt: classical and modified orthogonalization:
Gram_Schmidt.m
(by M. Peszynska)
- demonstration of teh loss and recapture of orthogonality in classical and modified Gram-Schmidt methods testgram.m (by D. Fettig, M. Peszynska)
- Conjugate Gradient Method:
mycgs.m
(by M. Peszynska)
- Numerical Methods for Differential and Partial Differential
Equations (MTH 452, 552, 453, 553)
- Introduction to MATLAB and Differential Equations worksheet 552-first.txt (by M. Peszynska)
- Forward Euler method demonstration FE.m (by M. Peszynska)
- Backward Euler method demonstration with Newton/Picard' iterative solvers BE.m (by M. Peszynska)
- How to use step Richardson's halving/doubling to get error estimates error_estimate_demo.m (by M. Peszynska)
- Template for solving a two-point Boundary Value Problem using point-centered finite difference method fd1d.m (by M. Peszynska)
- Template for solving a two-point Initial Boundary Value Problem using point-centered finite difference method and backward Euler discretization in time fd1d_heat.m (by M. Peszynska)
