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Based on these studies a kernel function is introduced that improves the stability of MPS method.
The weights are assigned by a kernel function whose bandwidth is chosen by cross-validation in terms of predictive loglikelihood.
The nonlinear regression model is derived by introducing a kernel function into the proposed linear regression model.
Backstepping transformations with a kernel function and a vector-valued function are introduced to design control laws.
Observations vector in the input space are transformed to feature space by way of a kernel function.
Integral type non-local elastic models phenomenologically incorporate microstructure information through a weighting function known as a kernel function.
Let (K x)) be a kernel function.
where Γ denotes a kernel function [13].
where K σ (z) is a kernel function.
In KDE, first, a kernel function is defined [23].
Pseudo codes for calling a kernel function and the operations inside a kernel function are shown in Fig. 5.
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