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radial kernel
相关语句
  径向核
     A THEOREM ABOUT POINTWISE CONVERGENT APPROXIMATE IDENTITY OF RADIAL KERNEL
     径向核的一个点态恒等逼近定理
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  “radial kernel”译为未确定词的双语例句
     Experiment validation has been carried out with iris image database,and the results show that the classification rate reaches to 98.55% for radial kernel function while keeping the stability of classification,and the classification rate is increased by 4.47% and 6.41% respectively compared with the nearest feature line method and dissimilarity function method.
     通过虹膜图像库的实验验证表明,该方法在保持分类稳定性的同时,获得了径向基核函数高达98.55%的分类率,该分类率比最近特征线方法和相异度函数方法的分类率分别提高了4.47%和6.41%.
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  相似匹配句对
     kernel technology?
     NET的实质和一些核心技术、.
短句来源
     ADAPTIVE RADIAL PARABOLA KERNEL REPRESENTATION AND ITS APPLICATION IN THE FAULT DIAGNOSIS
     自适应径向抛物线核时频分布及其在故障诊断中的应用
短句来源
     Radial Bogis
     径向转向架
短句来源
     The kernel functions are generated to use polynomials and radial basic functions.
     核函数分别采用多项式和径向基函数。
短句来源
     (2) the radial gallery.
     (2)径向坑道。
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  radial kernel
In this article, we therefore develop an alternative algorithm called iterative metric adaptation for radial kernel functions (IMAK), which is theoretically better justifiable within the NGCA framework.
      
A new algorithm of non-Gaussian component analysis with radial kernel functions
      
The radial kernel width factor has been determined by increasing it, until CYP51 has been classified correctly.
      
The radial kernel is a popular choice in the SVM literature.
      
The SVM specification in turn is based on a radial kernel.
      


In order to improve the accuracy and stability of iris image classification,an iris image classification method was developed based on minimax probability machine.The classification maximization was realized through controlling minimal error of the classification probability and expanding two-dimension classification to multi-dimension iris feature space.The iris multi-dimension classification problem with different kernel function is solved through mapping iris features to high dimension space,which possesses...

In order to improve the accuracy and stability of iris image classification,an iris image classification method was developed based on minimax probability machine.The classification maximization was realized through controlling minimal error of the classification probability and expanding two-dimension classification to multi-dimension iris feature space.The iris multi-dimension classification problem with different kernel function is solved through mapping iris features to high dimension space,which possesses the features of high classification rate and strong stability.Experiment validation has been carried out with iris image database,and the results show that the classification rate reaches to 98.55% for radial kernel function while keeping the stability of classification,and the classification rate is increased by 4.47% and 6.41% respectively compared with the nearest feature line method and dissimilarity function method.

为了提高虹膜图像分类的准确性和稳定性,提出了一种基于最小最大概率机的虹膜图像分类方法.该方法通过控制错分概率实现分类的最大化,将一般的二维分类问题扩展到虹膜特征的多维空间,并利用最小最大概率机的高维映射泛化特性,实现了不同核函数下的虹膜图像多维分类问题,具有分类准确率高、稳定性好的特点.通过虹膜图像库的实验验证表明,该方法在保持分类稳定性的同时,获得了径向基核函数高达98.55%的分类率,该分类率比最近特征线方法和相异度函数方法的分类率分别提高了4.47%和6.41%.

Because the effect of profile control is influenced by various factors, thus it is hard to establish the relationship between the profile control and each factor. A relation model between the profile control effect and each factor is established by using radial kernel function based on support vector machine. Models based on different support vector machines are established by using the indexes, such as dimensionless oil increment and reduction of water content, the implemented profile control measures...

Because the effect of profile control is influenced by various factors, thus it is hard to establish the relationship between the profile control and each factor. A relation model between the profile control effect and each factor is established by using radial kernel function based on support vector machine. Models based on different support vector machines are established by using the indexes, such as dimensionless oil increment and reduction of water content, the implemented profile control measures are used as a learning sample to build corresponding models, they are used to predict the indexes stated above. Inspection of the models indicates that the inspection error is controlled within 10 with higher precision.

因调剖措施效果受多种因素的影响,很难在调剖措施效果和各个因素之间建立一种确定的关系。利用支持向量机方法,采用径向基核函数,建立了调剖措施效果与各个因素之间的一种关系模型,分别以无因次增油量、含水率的下降等评价指标建立不同的支持向量机模型,利用已实施的调剖措施作为学习样本来获得相应的模型,分别用于对无因次增油量、含水率的下降等指标进行预测。该模型的检验过程表明,检验样本的平均误差控制在10%以内,具有较高的准确率。

 
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