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Specifically, after source modeling (three spheres BERG method as conductive head volume, weighted minimum norm constraint applied to an "empirical" Bayesian approach), non-parametric bootstrap-based statistical analysis was performed to extract the significant spatiotemporal pattern of the TMS-evoked responses.
This minimum norm constraint has two effects on the solution (22) that was obtained in the noiseless case.
The extent to which the zeros are displaced as compared to the noiseless solution depends on the noise power which determines the relative importance of the minimum norm constraint in the LP criterion (13).
It can, hence, be seen that this term acts as a minimum norm constraint in the LP criterion, in the sense that it penalizes the squared norm of the PEF impulse response coefficient vector: (24).
The angular effect described above can also be observed in the noiseless case when the LP model order, in which case the "extraneous" PEF zeros tend to be uniformly distributed around the unit circle if a minimum norm constraint is incorporated in the LP criterion [45].
In the case if minimum norm solutions the main disadvantage is that they tend to assign observed activity to cortical areas because they are closer to the sensors and thus they fit better to the minimum norm constraint.
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The inverse solution problem was stabilized by the minimum norm mathematical constraint: Out of the many current distributions that could account for the recorded sensor data, the solution with the minimum L2 norm (i.e., the minimum total power of the current distribution) was used.
This in turn makes it possible to select the output feedback matrix with minimum norm or other constraints.
To compute the estimates of the sources, a minimum norm solution with the LAURA (local autoregressive average) constraint [ 26] was employed.
This point x ¯ is also a unique minimum norm common solution of fixed point and split equilibrium constraints: Find min q ∈ Fix ( T ) ∩ Ω ∥ q ∥.
Applying Theorems 2.2 and 4.1, Lemma 4.1, we can find the unique minimum norm common solution of fixed point and split equilibrium constraints and the solution of mathematical programming with fixed point and split equilibrium constraints.
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