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For example, the block Toeplitz matrices corresponding to covariances of a stable singular AR model with dimensions high enough will be singular and thus only positive semidefinite.
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We selected an optimal model with dimension of neural network 35*35 and number of learning epochs equal to 200.
The geological model (Fig. 9) for our study zone extracted from Baillieux (2012) is derived from seismic and borehole data and consists in a 6 layer model with dimension ~30 × 20 × 5 km.
Recently, several multiscale methods [20 23] are proposed to simulate models with dimensions of the order of microns and thus minimize the possibility of the contamination of the results by the boundary conditions arising from the small model size.
A series of pool fire tests was conducted using a flat, unconfined model ceiling with dimensions of 2.5 m (D ×3.0 m (L) and changing the ceiling inclination angle of up to 40°.
The highest prediction power was obtained for models with dimension 35*35.
In order to evaluate the functions f 1, f 2, and A for models with dimension larger than two, we need to calculate d ζ / d θ.
Statistical performance of models with dimension 35*35 depending on number of learning epochs is represented on Figure 1 and Figure 2 for models with MDL (model A) and Dragon (model B) descriptors correspondingly.
In fact, six dimensions must be fitted in the reduced rank form (FARR6) to produce equivalent likelihoods to the best FA model with three dimensions.
This study developed an integrated model with six dimensions: learners, instructors, courses, technology, design, and environment.
A total of 20 experiments were conducted using the scaled 3-D physical model with 30×30×6 cm3 dimensions.
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