We show that the convergence of both projection methods is controlled by the ability of the spectral framework to approximate correctly the steady Stokes problem.
Verifying a computer simulation means checking that the equations of the model are being correctly approximated.
With TTrain = 5, only 6.5% of the papers left the prediction envelope 30 years later; hence, the model correctly approximated the citation range for 93.5% of papers 25 years into the future.
It is well-known that the elements ϕ j k of g j k ( j = 1, 2, …, N k ), which are g i belonging to cluster k, can be correctly approximated in their nonlinear eigenspace in the least-squares sense.
Depending on the mosquito collection method used (human landing, light trap, etc)., the human-biting rate can be correctly approximated either by the number of blood meals taken on humans/mosquito/day or by the mosquito density.
Therefore, because the reflection patterns are diffuse, they can correctly be approximated using the Lambertian reflection model.
It is known that the reflection pattern of most surfaces can correctly be approximated using the Lambert or the Phong models.
ALBNN correctly approximates a target hypothesis by both considering the interaction between two procedures and minimizing individual procedure errors.
It is demonstrated that (i) the model correctly approximates the observations and (ii) material parameters are independent of strain rate and change consistently with temperature.
This does not come as a complete surprise since some of the images, such as Wood1, Wood2, Lampshade1, and Lampshade2 contain only few useful spatial features for approximating the disparity correctly.
