Solving the linear system: Iterative methods

This lecture covers iterative methods for solving linear systems, where approximate solutions are built to the actual system. It explains error and residual vectors, convergence criteria, and point-iterative methods like Jacobi, Gauss-Seidel, and Successive Over-Relaxation. The lecture also delves into examples of 1D steady diffusion, multigrid methods, and the concept of combining iterations on meshes of different sizes to improve accuracy and convergence rate.