As a function of the medium convergence μ A the temporal evolution of the system shows three distinctive behaviors.
As was done by Mastroberardino in[3], the residuals have been plotted as a function of r for the optimal values of the convergence control parameters C1, C2, C3 and c1, c2, c3 (given in Tables 1,2 and3) anotnot as a function of these convergence control parameters for a fixed value of r as this is a better illustration of convergence.
Figure 7 illustrates the typical convergence pattern of a single LED coefficient (L850 in this example), as a function of the iteration number c. Convergence of coefficients of the remaining LEDs in the array follows a similar pattern.
Figure 2 The convergence of as a function of the number of iterations.
As in the previous case, we test the convergence behavior as a function of the parameter ϵ abs (left panel) and the supercell size (right panel).
Effectiveness of multi-direction search on total energy convergence as a function of the number of iterations for a C atom with the 6-31G** baset set is shown.
Figure 3 E shows the average synaptic convergence as a function of the network size.
The Geweke and Gelman and Rubin diagnostics can be plotted as a function of iteration to determine the progress of convergence as a function of the number of iterations.
The convergence of the method as a function of the extraction degrees of the false components has been studied.
First, we consider the convergence of the synchronization metrics as a function of the training sequence length.
