Sentence examples for norms of data from inspiring English sources

The electronic database applications have been designed in accordance with the norms of data protection in force and guarantee the security access pursuant to Ley Orgánica 15/1999, de 13 of December [ 15].

One way to objectively choose (alpha ^2) is by plotting the norm of the model vector, (||{varvec{m}}||/{text {max}}(||{varvec{m}}||)) (individually normalized to the range between 0 and 1 for better comparison between different orbits) versus the norm of data misfit, (||{varvec{Gm}}-{varvec{d^{{mathrm{obs}}}}}||) for various values of the regularization parameter (alpha ^2).

where depends on the norms of initial data given in Theorem 1.1, but not on.

Thus, we get the maximal L p - L q regularity result: ∫ 0 ∞ e − p γ t { ∥ ( p + ( ⋅, t ), ∂ t p + ( ⋅, t ) ) ∥ W q 1 + ∑ ℓ = ± ( ∥ ∂ t u ℓ ( ⋅, t ) ∥ L q + ∥ u ℓ ( ⋅, t ) ∥ W q 2 } p d t ≤ C { suitable norms of initial data and right members in (1.6) } ( 1 < p, q < ∞ ). for some positive constants γ and C with help of the Weis operator valued Fourier multiplier theorem [14].

Standard metrics for airborne topographic lidar are important to enable objective and quantitative evaluation of lidar systems and data, evaluation and comparison of emerging technologies, and specification of industry norms for data quality.

The fit of the model to the data was measured by the RMS error of the model with respect to the data normalized with respect to the norm of the data itself.

In fact, a few companies are challenging the norm of corporate data hoarding by actually sharing some information with the customers who generate it — and offering tools to put it to use.

This is due to the fact that the DCT matrix is unitary and preservesℓ2-norm of the data.

The proof of the first estimate follows from the asymptotic behavior of H i together with the assumption on the norm of boundary data φ given by (30).

One of the most intriguing questions regarding the L p -normed fitting is how can we determine the characteristic p-norm of the data.

The inverse solution simultaneously minimizes the L-2 norm of the data misfit and the model roughness: (1 where the first term ǁGm − dǁ2 is the L-2 norm of the data misfit and the second term ε−2ǁLmǁ2 is a measure of the model roughness.