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1)  radical basis kernel
径向基核
1.
The experiment also shows that,linear kernel has the smallest time consumption;radical basis kernel has the best accuracy with small feature num,which is lower than linear kernel with large feature num.
同时表明,线性核时间消耗最小,径向基核在特征数目较小时,具有最好的识别率,而在特征数目较大时,线性核最优。
2)  radial basis function
径向基核函数
3)  RBF kernel function
径向基核函数
1.
The theory of SVM is studied at first,then an ameliorated RBF kernel function is presented,based on which an improved kernel function pattern classification method of SVM is put forward.
首先分析了支持向量机原理,随后引入一种改进的径向基核函数,在此基础上,提出了一种改进核函数的SVM模式分类方法。
2.
Based on the conclusion, we put forward the idea of using the covariance function as a substitute for the RBF kernel function of SVM.
考虑到在某些情况下协方差函数可能不存在 ,因此考虑用变异函数来代替协方差函数估计径向基核函数的宽度参数 。
4)  parallel RBF kernel
并行径向基核
5)  radial Gaussian kernel
径向高斯核
1.
This paper starts from analyzing the limitation of time frequency distribution with fixed kernel, and gives analyses of data adaptive flexible window STFT, signal dependent radial Gaussian kernel time frequency representation and matching pursuit time frequency distributions, and then introduces the physical consideration and the mathematical base of the Chirplet Transform.
从分析固定核函数的时频分析法对分析信号的局限出发 ,引出基于数据的变窗长STFT分析、基于信号的径向高斯核时频分析、自适应配投影时频表示 ,简述了Chirp let变换的物理意义和数学基础。
6)  multi-kernel-parameter support vector machine with RBF kernel
多核参数径向基支持向量机
1.
On the basis of this conclusion, an improved multi-kernel-parameter support vector machine with RBF kernel based on genetic algorithm was proposed, where genetic algorithm was applied to find optimum ker.
此结论基础上,提出了一种基于遗传算法的多核参数径向基支持向量机算法,通过遗传算法最小化验证误差,实现了根据各个特征的识别能力赋予其不同大小的核参数。
补充资料:原子径向分布函数
分子式:
CAS号:

性质:电子出现在半径为r的球面附近单位厚度球壳内的概率,以符号D(r)表示。通常定义D(r)为:D(r)=4πr2R2(r),其中R(r)为原子轨函中的径向部分。它反映电子云的分布随半径r的变化情况。对氢原子而言,径向分布函数最大值在r等于玻尔半径α0处,在此意义上可以说玻尔轨道是氢原子结构的粗略近似。

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