To show the convergence results of EMFM method, we require to show that the updating matrix [B.sub.k] is bounded above and below by some positive constants.
One can observe that EMFM has the smallest number of iterations compared to the classical diagonal updating (I-VDN) proposed by Waziri et al.
If we compare the performance of all methods, in terms of CPU time, it is clear that EMFM method consumes less CPU time than the others and still keeping memory requirement and CPU time in seconds to only 0(n).All five methods are able to obtain the solution ([x.sup.*] = -1.1243,1.5001) of A2, but EMFM method consumes less CPU time in second (0.001) compared to the other 4 methods.
EMFM method has very good solving speed and the best performance among the Newton-like methods.
The electric properties of the EMFM sensor channel in the electrode signal expression are evaluated by the virtual current density [1, 2].
Dependently on the EMFM metrological properties we can suppose that the active zone is composed of all sensor points in which B[perpendicular to] [greater than or equal to] (0,01 - 0,005) B[[perpendicular to].sub.max].
He introduces this parameter nominally, as current density in the active zone with moveless fluid when current source with [I.sub.0] = 1 A is connected to EMFM sensor electrodes.
When the fluid flows with velocity v inside EMFM sensor and it intersects the lines of the magnetic field with magnetic flux density B, the electric field [E.sub.F] arises.
However, the readers of EMFM
are likely to find the following observations of great interest, at least as concerns the somewhat changing economic wisdom of the day and its ability to lead to the common good: