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.
论文第四章重点介绍用非线性映射方法分析原核生物基因密码子使用情况并得到的相关结论。
In chapter IV, the codon usage preferences in prokaryotic organism are analyzed by nonlinear mapping method.
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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