Sentence examples for containing the values of from inspiring English sources

The descriptor is constructed from a vector containing the values of all the orientation histogram entries.

where, this time, ψ is a vector containing the values of the variable θ ζ, t) in different points of the space and at different moments in time.

Let S R γ, P D R γ, and L I γ be vectors containing the values of SR, PDR, and LI, respectively, for a given γ obtained with different runs.

When comparing (18) and (2), and considering (3), it can be seen that the columns of correspond to the columns of, the matrix containing the values of the room transfer function for each frequency, up to an arbitrary scaling of column vectors and a reordering of sources, which is constant over frequencies after the permutation correction.

In our case the chromosome is a string containing the values of the layer thicknesses of the ITO/TiN structure: for example for M layers, the chromosome is a string containing M genes {d1, d2, d3, d4, …, dM} where di is the thickness of the generic i-th layer (from top to bottom) (see Fig. 2).

where r ~ j = r 1 j, ⋯, r Q j T is a vector containing the values of Q selected neighboring coarse-resolution pixels, w ~ j represents a vector of the unknown fine-resolution pixels contained in the Q coarse-resolution pixels, and Φ ~ j is a Q × QN2 sensing matrix, whose (q,n th element is ϕ q, n j = A j x q - x n, y q - y n ⋅ exp i x n k xc j + y n k yc j, (15).

Training neural networks typically involves supervised learning, where each training example contains the values of both the input data and the desired output.

(M1) matrix contains the values of Extended Mahalanobis distances between the components of weak weights.

(M2) matrix contains the values of Extended Mahalanobis distances between the components of medium weights.

Each row ({mathbf {Z}} _{icdot }) contains the values of the empirical cdf of ({mathbf {V}} _{icdot }).

(M3) matrix contains the values of Extended Mahalanobis distances between the components of strong weights.