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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Two-level-classifier is designed to recognized urinary sediments. The kernel function uses the radial basis function and grid-search method is used to select the parameters of SVM.

在设计时，采用两级SVM分类器级联的方式，核函数采用径向基函数，并且用网格搜索法来选取合适的参数。

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This paper presents an adaptive algorithm of optimally determining the structures, number, positions and widths of kernel functions of the improved radial basis function (IRBF) neural networks.

本文提出了改进的RBF神经网络结构、核函数个数、位置与宽度优化算法。

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