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The central portion of the software expression of a mathematical algorithm, as in computed tomography.
[O.E. cyrnel, a little corn]
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Thus we construct the following kernel function based on Gaussian to map the data to high dimensional kernel space:
It is obvious that constructing a suitable reproducing kernel spaces and effectively calculating the reproducing kernel expression become the key to apply reproducing kernel Hilbert space method.
From Figure 2, we can easily know that the LGECSDL algorithm has achieved better recognition results in Hellinger kernel space. With the parameter a varied from [2.sup.-13] to [2.sup.-3], the recognition rate increased gradually and then decreased.
This filtering mechanism is an efficient way of filtering packets in the kernel space and it is being used today in hardware networking equipment and even in virtual networking software such as OVS, employed mainly to overcome the limitations of OpenFlow regarding packet classification.
It can learn a set of optimized sparse representations as well as dictionaries in a multiview kernel space. We consider label view (or tag view) as an additional view and adaptively utilize the relationship between label views and visual feature views to find the more discriminative sparse representation by incorporating multiview learning and the [L.sub.1,2]-norm joint sparsity.
In this paper, the RKHS method was employed successfully for solving a class of second-order Fredholm IDEs by constructing a reproducing kernel space in which each function satisfies the given boundary conditions of the considered problems.
In view of the completeness of the reproducing kernel space, [y.sub.n](x) [right arrow] y(x) as n [right arrow] [infinity].
In this work, we design an intelligent abnormality detection and fault recognition technique for the exhaust system of gas turbines based on information entropy, which is used in measuring the uniformity of exhaust temperatures, evaluating the significance of features in kernel spaces, and selecting splitting nodes for constructing decision trees.
Geng, "Solving singular two-point boundary value problem in reproducing kernel space," Journal of Computational and Applied Mathematics, vol.
Therefore, KICA can be thought as performing ICA in the whitened kernel space generated from KPCA.
Since we use an implicit document representation, we need to test all document pairs during the kernel evaluation, thus, unless we apply a feature selection in the kernel space, the complexity of point 1 cannot be improved.
The fault protection that Sun is working on is keeping faults in the zones from creeping into the Solaris kernel space. A memory leak from a single C++ application running in one zone, for instance, should not be able to crash a whole system.