Sentence examples for minimizing the squared from inspiring English sources

Exact(38)

For nonlinearly separable classes linear classifiers were optimally designed, for example, by minimizing the squared error.

Two estimation methods are used: 1) minimizing the squared difference between the observed records and the modeled biological frontier and 2) using extreme value theory to estimate the biological frontier that maximizes the probability of observing the existing world records by age.

The optimal power distribution can be obtained by minimizing the squared η2 in (23) with respect to λ under the constraints that (28).

In the presence of model mismatch, (46) is no longer satisfied exactly, yet minimizing the squared Euclidean norm ∥R h∥2 subject to ∥h∥2=1 gives a good estimate for h [41].

Therefore, it is possible to retrieve these spread values by minimizing the squared Frobenius norm of the difference between the model signal and the signal generated out of the image on the circular antenna.

Note that, although (11) and (12) are equivalent problems (i.e., with the same solution), they are different because in the latter case we are minimizing the squared norm of Df(x).

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Similar(21)

We introduce a new minimization that simultaneously minimizes the squared flows and the squared differences between flows.

We therefore minimize the squared scaled error sum E tA, ΔTA2) = Σi ei2(1+αi2) which is a weighted least squares problem in the variables (tA, ΔTA2) [79] (Fig 13B).

To find a best match, the observed foundress numbers and the simulated foundress numbers are binned in ranges: 1 3, 4 6, >6, with the best match being that which minimizes the squared deviations between observed and simulated distributions.

The Jenks method minimized the squared deviations of the class means and set boundaries where relatively large spaces between exposure metric values occurred.

Landmark configurations are translated, scaled and rotated so as to minimize the squared, summed distances between the corresponding landmarks of each individual and the mean [ 26].

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