The comparison of different kernel functions for SVM shows that RBF kernel function is most suitable for recognition of grape disease.

不同分类核函数的相互比较分析表明，径向基核函数最适合于葡萄病害的分类识别。

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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。

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The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel.

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；

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