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It will be shown that the probabilistic (Bayesian) approach reduces the number of test points required in providing a flutter speed estimate for a given accuracy and precision.
The basic idea is to rewrite the failure probability estimate for a given set of random samples in simulation as a function of the distribution parameters.
About floods, one will estimate, for a given river cross-section, whether the probability that the discharge would exceed a given threshold or, symmetrically, the discharge which has a given probability of exceedance.
A linear matrix inequality (LMI) approach is developed to estimate, for a given controller and a given finite-level quantizer, a set of admissible initial states and an associated attractor set in a neighborhood of the origin such that all state trajectories starting in the first set will converge to the attractor in a finite time and will never leave it.
The mean impact across states is obtained by weighting the estimate for a given state by the number of participants who were matched in that state, providing the average impact for matched WIA participants.
It is straightforward to figure out that there is no need to form cost volume in order to obtain the depth estimate for a given coordinate x at the i th iteration.
Similar(41)
Then production rates can be reasonably estimated for a given set of conditions.
First the temperature distribution over the depth of the slab is estimated for a given fire scenario.
With the calculated recovery removal-functions the possible recovery removal-functionsmathe for a given removal rate for the limited compossible
YL was estimated for a given cultivar as the difference between the mean yield of fungicide-protected and of untreated plots.
This arbitrary treatment of key inputs and parameters can lead to inconsistencies and significant bias in flood estimates for a given average recurrence interval.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com