不同分类核函数的相互比较分析表明，线性核函数最适合黄瓜病害识别。
The comparison of different kernel functions for SVM shows that liner kernel function is most suitable for recognition of cucumber disease.
不同分类核函数的相互比较分析表明，线性核函数最适于植物病害的分类识别。
The comparison of different kernel functions for SVM shows that liner kernel function is most suitable for shape recognition of plant disease spot.
综合考虑SVM的学习能力、外推能力及寻优时间，决定选择线性核函数作为SVM在柴油机尾气分析中的核模型。
Considering the learning and extrapolating ability as well as the parameter optimizing time, linear kernel is determined to be used in SVM in the analysis of diesel engine exhaust emissions.
通过引入核函数，支持向量机可以很容易地实现非线性算法。
SVM can deal with nonlinear problems in classification and Regression easily by using kernel functions.
通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
对于线性不可分的样本空间，需要寻找核函数，将线性不可分的样本集映射到另一个高维线性空间。
As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space.
又由于采用了核函数思想，使它把非线性空间的问题转换到线性空间，降低了算法的复杂度。
Moreover, by using the kernel function idea, this theory can change the problem in non-linearity space to that in the linearity space in order to reduce the algorithm complexity.
核口袋算法的特点是用简单的迭代过程和核函数来实现非线性分类器的设计。
Its advantage is to implement a nonlinear classifier using a simply iterative procedure and kernel functions.
首先，用具有RBF核函数的LS-SVM离线建立被控对象的非线性模型；
The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel.
尽管核函数方法可以提取到非线性特征，但该方法并不一定能很好的降维。
Although the method based kernel functions can extract nonlinear features, it is not good to reduce dimension.
算法采用核函数变换的方式，将重叠严重和非线性的光谱数据进行高维空间变换后再计算各组分气体浓度。
The transformation of kernel function is used to solve the overlapped mixed gas feature absorption spectrum in high dimension space.
提出了一个基于核函数的后非线性盲分离算法。
We derive a new method based on kernel to solve the post-linear blind signal separation problem.
又由于采用了核函数思想，使它将非线性问题转化为线性问题来解决，降低了算法的复杂度。
Moreover, SVM can convert a nonlinear learning problem into a linear learning problem in order to reduce the algorithm complexity by using the kernel function concept.
又由于采用了核函数思想，使它把非线性问题转化为线性问题来解决，降低了算法的复杂度。
Moreover, SVMs can change a nonlinear learning problem in to a linear learning problem in order to reduce the algorithm complexity by using the kernel function idea.
该方法通过计算齿轮振动信号原始特征空间的内积核函数来实现原始特征空间到高维特征空间的非线性映射。
In this approach, the integral operator kernel functions is used to realize the nonlinear map from the raw feature space of gear vibration signals to high dimensional feature space.
该方法通过计算齿轮振动信号原始特征空间的内积核函数来实现原始特征空间到高维特征空间的非线性映射。
In this approach, the integral operator kernel functions is used to realize the nonlinear map from the raw feature space of gear vibration signals to high dimensional feature space.
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