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The essential features of the algorithm are as follows: A kernel modification algorithm is constructed according to the conformal mapping of information geometry and the modified kernel function is subsequently used to train the classification algorithm in support vector data description.

该算法的核心思想为:根据信息几何中保角映射的方法构造数据驱动的核函数修正算法,然后再利用修正的核函数训练支持向量数据描述分类算法。

For reasons that it is difficult to develop a non-linear model for the evaluation of the fabric drap and the conventional evaluation method can not achieve the desired accuracy of it.

针对织物悬垂性评估中存在非线性建模困难及评估精度不高等问题,结合织物悬垂性参数数据的特点,基于Mercer核函数的性质,构建Mercer核函数的织物悬垂性评估模型。

The penalty function is adopted to impose the essential boundary condition, the tensor product weight function with a rectangular influence domain is chosen, and the finite element background cell is considered as the integration unit.

将无网格再生核质点法用于刚塑性可压缩材料轧制过程的模拟,采用罚函数满足本质边界条件,选用矩形影响域的张量积核函数,利用有限元网格作为积分单元,对求解域内和边界上采用不同的高斯积分方案。

All this can tell us how to create new kernels, choose suitable parameters and improve these existing kernels.

为构造适合文本分类的新的核函数、文本分类中的核参数的选择和改进现有的核函数提供了很好的指导。

In this thesis,the main problem investigated is the relationship between Hilbert spaceH which {ei}ni=1 let be an orthonormal basis and the kernel by making use of the properties of the kernel of H.

笔者主要研究了以{ei}in=1为正交基的再生核Hilbert空间H中的核函数的一些性质,并通过这些性质简要的描述了Hilbert空间H与它的核函数之间的关系。

The traditional mean shift algorithm requires a symmetric kernel, such as a circle or a rectangle, and assumes that the target's scale is symmetric during the course of tracking. The pixels are used on the edge as the samples, about 5% to 10% of the total pixels in the kernel.

与采用对称核函数的均值迁移目标跟踪算法相比,采用目标边缘点作为核函数中的样本点,参与计算的样本点为核窗口中样本的5%~10%,使图像处理速度达到了50帧/s以上,满足了实时跟踪的要求。

The traditional mean shift algorithm requires a symmetric kernel, such as a circle or a rectangle, and assumes that the target's scale is symmetric during the course of tracking.

与采用对称核函数的均值迁移目标跟踪算法相比,采用目标边缘点作为核函数中的样本点,参与计算的样本点为核窗口中样本的5%~10%,使图像处理速度达到了50 帧/s 以上,满足了实时跟踪的要求。

Sinceβkernel is non-symmetric, there will be problem in the precision of graduation if using kernel graduation method, because, generally, kernel function is supposed to be symmetric in kernel graduation method, thus will cause boundary deviation in actual application.

但β核为非对称核,如果使用核修匀方法,在修匀精度上仍会存在问题,因为一般核修匀方法中均假设核函数具有对称性,在实际应用中将导致出现边界偏差现象。

Different from the existing kernel feature extraction methods, the kernel function used in the proposed one is not required to satisfy Mercers theorem so that they can be chosen from a wide range.

与现有的核特征抽取方法不同,该方法不需要核函数满足Mercer定理,从而增加了核函数的选择范围。

Researches on kernel clustering algorithms. After combining K-means clustering algorithm and the theory of kernel-based learning algorithms, we propose a fast kernel K-means clustering method which is based on CPD kernel. The experiment results indicate that the clustering effect of the algorithm is better than that of K-means algorithm, the clustering speed of the algorithm is also fast than that of K-means algorithm.

核聚类算法的研究:探讨了K-均值聚类算法,通过将核学习理论与K-均值聚类算法结合,提出了一种基于CPD核函数的快速核K-均值聚类算法,并将该算法与基于Mercer核的核聚类算法进行了比较,实验结果显示,我们的方法不仅比K-均值聚类算法的聚类效果好,而且聚类速度快。

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