§ Home ranges estimated by 50% multi-annual kernels; climate variables measured at kernel centroid; † Temporal scales relate to time of measurements; B relates to birth year & C to capture year.
As a result, we can conclude that the proposed adaptive kernel with variable Gaussian core targets noise in each window over the whole image with a variable smoothing strength and kernel location.
The proposed approach uses a Gaussian kernel with variable width and direction called adaptive Gaussian kernel (AGK).
This concept inspired the development of soft margin MKL, which instead introduces kernel slack variable for each of the base kernels [39].
In this paper, the soft margin MKL algorithm introduced by Xu et al. [39] is adopted, where a kernel slack variable is first introduced for each of the base kernels when learning the kernel.
The experimental design which yielded the most satisfactory results comprised texture measurements from the combined area of 20 kernels and variables from seven channels input into the neural network.
On the other hand, as a related vector-valued singular integral with variable kernel, the Marcinkiewicz singular with rough variable kernel associated with surfaces of the form is considered.
Since the kernel of the variable-order operators has a variable exponent, analytical solutions to variable fractional-order differential equations are more difficult to obtain.
where b → = ( b 1, …, b n ), b i ∈ BMO, 1 ≤ i ≤ N. The variable kernel K ( x, ξ ) depends on some parameter x and possesses 'good' properties with respect to the second variable ξ, which was firstly introduced by Fabes and Rieviève in [1].
Recently, Xue and Yabuta [7] studied the boundedness of the operator with variable kernel.
