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Theoretical exercise sheet 2
Linear systems
Exercises 1 and 5 (marked *) to be submitted via *Crowdmark* in pdf
format (either handwritten and scanned, or typeset using LaTeX).
EXERCISE 1(*) Let.
(a) The Jacobi and Gauss-Seidel methods for the approximation of the solution to the linear
system Ax = b can both be written in the form
Pxk+1 = Nxk + b.
Write down the matrices P and N for each of the two methods. What are the associated
iteration matrices BJ and BGS?
(b) Compute the vector x1 obtained after one iteration with the Jacobi method starting from
the initial vector x0 .
(c) Do both methods converge? Which gives the iteration matrix with the smallest spectral
radius?
(d) Prove that both methods converge linearly with respect to the norm ‖ · ‖∞, and compare
the convergence constants.
EXERCISE 2 Let.
(a) Write the Gauss-Seidel method for the solution of the linear system Ax = b. What is the
associated iteration matrix BGS?
(b) What can be said about the convergence of the Gauss-Seidel method for this system?
(c) Now consider the iteration
D(xk+1 ? xk) = αrk k ≥ 0,
where D is the diagonal of A and rk = b?Axk is the residual. This method is sometimes
called the Jacobi over-relaxation (JOR) method; note that for α = 1 the method is
equivalent to the Jacobi method.
Write down the associated iteration matrix BJOR, and find the optimal choice of α min-
imising the spectral radius ρ(BJOR).
(d) Starting from the initial vector x(0) = (1, 1)T , compute the first iteration x1 of the JOR
method using the optimal choice of α you derived in part (c).