1.II.38C

Numerical Analysis
Part II, 2006

(a) Define the Jacobi method with relaxation for solving the linear system Ax=bA x=b.

(b) Let AA be a symmetric positive definite matrix with diagonal part DD such that the matrix 2DA2 D-A is also positive definite. Prove that the iteration always converges if the relaxation parameter ω\omega is equal to 1 .

(c) Let AA be the tridiagonal matrix with diagonal elements aii=1a_{i i}=1 and off-diagonal elements ai+1,i=ai,i+1=1/4a_{i+1, i}=a_{i, i+1}=1 / 4. Prove that convergence occurs if ω\omega satisfies 0<ω4/30<\omega \leqslant 4 / 3. Explain briefly why the choice ω=1\omega=1 is optimal.

[You may quote without proof any relevant result about the convergence of iterative methods and about the eigenvalues of matrices.]