Multigrid Methods For Problems With Many Variables, Especially Numerical Solution For Elliptic Partial Differential Equations. The Motivation and Applications Arise From Various Fields of Scientific Computing, Including Image Processing And Analysis. Topics Are# Basic Concepts, Local and Global Processing, Discretization, 1d Model Problem and Its Direct and Iterative Solution, Convergence Analysis, 2d Model Problem, Survey Of Classical Relaxation Methods, Error-smoothing By Relaxation, Grid-refinement, Two-grid and Multigrid Algorithms, Fourier Analysis of Convergence, Ellipticity and H-ellipticity, Nonlinear And Anisotropic Problems, Advanced Techniques, Algebraic Approach, Applications.

Faculty: Computer Science
|Undergraduate Studies |Graduate Studies

Pre-required courses

234107 - Numerical Analysis 1 or 234125 - Numerical Algorithms

Course with no extra credit

238790 - Multigrid Methods

Semestrial Information