link to my thesis

7.5. NUMERICAL EXPERIMENTS WITH JDCOMM SOFTWARE 123
Figure 7.7: Residual norms against MVs with A p1
for the JD and JDCOMM methods
also perform better than the conventional JD method in terms of required flops and
computation time. To compare this performance with SOSTOOLS and GloptiPoly:
both methods compute the same global optimum and same location as found with
the JD methods and require 114 and 122 seconds respectively.
7.5.3 Experiment 3
In the previous two experiments, we were looking for the smallest real eigenvalues of
the matrix A p1 which were located on the outside of the eigenvalue spectrum. See
Figures 7.4 and 7.8. Finding an eigenvalue at the outside of the spectrum is relatively
easy for a Jacobi–Davidson type method. When the required eigenvalue lies more in
the interior of the spectrum, computation becomes more difficult in the sense that
the choice of parameters for the Jacobi–Davidson method plays a more important
role as will be shown in this experiment.