Sentence examples for kernel initial from inspiring English sources

The method is based on the generalized polynomial chaos (gPC) approximation in the stochastic Galerkin framework, and can handle random inputs from collision kernel, initial data or boundary data.

But it is possible that extra derivatives are needed if the kernel (initial conditions) is not informative, thus zero or dependent Lie derivatives are generated.

The new feature results in lower statistical noise for simulating two-component coagulation, which is validated by using two-component coagulation cases for which analytical solutions exist (a discrete process with sum kernel for initial monodisperse populations and a process with constant kernel for initial polydisperse populations).

We make the following standing hypotheses concerning the kernel and initial history of (1.1) and (1.2). (3.1).

The proposed technique has been tested for pure growth, simultaneous growth and aggregation, and simultaneous nucleation and growth for a large number of combinations obtained by changing functions for nucleation rate, growth rate, aggregation kernel and initial condition.

Different kernels and initial conditions were tested.

In order to test the robustness of the rule-set, simulations carried out with pivotwise expansion of X-grid are compared with those obtained using sufficiently large fixed X-grids for a number of composition independent and composition dependent aggregation kernels and initial conditions.

Based on the this initial kernel k p, intermediate derived kernel k q is computed on top of the layer q and this in turn is used to compute the final derived kernel k r on the top most layer r, which can help us in the classification of the whole images in layer r.

After this criterion has been checked then we select a node to be added to the module, if it satisfies the following: (4) W v u i ≤ p 2 ⋅ β G I N T (v ) G is the final module that is built from the initial kernel (i.e. initially G = Ks), we select the constant p2 to be anywhere between 0.9 and 1.0 (in the specific study we have set the value of p2 to 0.9).

Computation of the initial kernel, the neural response and the derived kernel is explained in detail in the following subsections and the overall pipeline of the methodology is shown in Figure 7. Let there be m templates (sequence motifs) q 1...q m in the bottom layer.

The benefit over simple adaptive solutions is that such kernels adapt to the structure of the input data; therefore, they are less sensitive to the initial kernel bandwidth selection.