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.
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。
Within a driver, the mmap function is implemented through the remap_pfn_range kernel function, which provides a linear mapping of device memory into a user's address space.
在一个驱动程序中，mmap函数通过remap _ pfn_range内核函数实现，它提供设备内存到用户地址空间的线性映射。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
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。
This paper analyzes the kernel matrix in the linear programming problem and proposes a new revised prime-dual algorithm based on the kernel matrix.
本文通过对线性规划问题中的核心矩阵的分析，提出了一种基于核心矩阵的原始对偶算法。
The main idea is to approximate the classical local linear embedding (LLE) by introducing a linear transformation matrix and then find the solution in a very high dimensional space by kernel trick.
其主要思想是通过引入线性变换矩阵来近似经典的局部线性嵌入(LLE)，然后通过核方法的技巧在高维空间里求解。
As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space.
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。
Sequence transformation is based on the principle of extrapolation, interpolating certain items by the kernel of the sequence, and finally is obtained by solving linear equations.
序列变换是依据外推法的原理，通过序列的核来插值序列的某些项，最后求解线性方程组得到的。
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, 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.
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。
We derive a new method based on kernel to solve the post-linear blind signal separation problem.
提出了一个基于核函数的后非线性盲分离算法。
So one should prefer non-linear models like SVM with kernel or tree based classifiers that bake in higher-order interaction features.
因此，每个人都应该选择适合高阶交互特征的带核SVM或基于树的分类器。
As principal component analysis mainly use the linear correlation of the data, we propose a nonlinear principal component analysis method, by combining the mercer kernel function with it.
主成分分析方法主要利用数据的线性相关性来降维，并不适合非线性相关的情况。
Aiming at this problem, this paper USES Kernel Locally Linear Embedding (KLLE) algorithm to solve image denoising problem in this paper.
针对该问题，提出基于核局部线性嵌入算法的图像去噪方法。
Aiming at this problem, this paper USES Kernel Locally Linear Embedding (KLLE) algorithm to solve image denoising problem in this paper.
针对该问题，提出基于核局部线性嵌入算法的图像去噪方法。
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