Sentence examples for evaluation of the kernel from inspiring English sources

The evaluation of the autocorrelation function is the key issue of the evaluation of the kernel basis functions.

Therefore, the number of operations needed to evaluate the volume integral is essentially equal to the number of operations needed to solve the differential equation on a rectangular region with a regular grid, and the method requires no evaluation of the kernel.

For a more discriminative evaluation of the kernels, we artificially enlarge the set of candidates: we use all molecular structures in KEGG with mass accuracy window [ μ M − Δ, μ M + Δ ] as candidates, where μ M is the true mass of the unknown molecule.

The norm of the centroid can be calculated using only the evaluations of the kernel on the inputs: (11).

The norm of the center can be calculated using only the evaluations of the kernel on the training sample inputs: Figure 8 Kwok and Tsang pre-image strategy.

While the dimension of the RKHS is usually very high (or even infinite), all relevant quantities are determined in terms of inner products (in the RKHS) between feature vectors, and can be efficiently computed in terms of a finite number of evaluations of the kernel function k (x, x ′ ) = 〈 ϕ (x ), ϕ (x ′ ) 〉.

For this reason, evaluation of the diffusion kernel was performed over a fixed grid of values of θ.

The latter is shown to simplify the Wigner Liouville kernel both conceptually and numerically as the spectral force Wigner Liouville equation avoids the numerical evaluation of the highly oscillatory Wigner kernel which is nonlocal in both position and momentum.

The accurate evaluation of fuel kernel Dancoff factors is needed when one analyzes nuclear reactors loaded with TRISO particle fuel.

The method is based on a standard symmetrized SPH expression for the viscous forces, which involves only first-order derivatives of the kernel through a direct evaluation of the viscous stress tensor.

The complexity of KDE is OKDE MN) evaluations (the kernel function, multiplications and additions), assuming N image pixels and M sample points (N pixels per image and M training images).