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kernel uclibc bootloader 的编译方法
- kernel uclibc bootloader 的编译方法-kernel uClibc build method Bootloader
kernel-process-control
- 核函数方法及其在过程控制中的应用研究,主要总结了我国与国外的核函数研究现状-kernel function method and the process control of applied research, the main conclusion of our country and abroad kernel Research
K_smooth
- The subroutines glkern.f and lokern.f use an efficient and fast algorithm for automatically adaptive nonparametric regression estimation with a kernel method. Roughly speaking, the method performs a local averaging of the observations when es
gkdj
- 以为高斯和密度估计，使用高斯核的非参数密度估计方法，对样本进行概率密度估计，程序中给出了窗宽的估算公式。-That the Gaussian and density estimation, using Gaussian kernel non-parametric density estimation method, the sample probability density estimates, the program gives the formula for bandwidth estim
KernelTracking
- A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kern
1
- 自适应核密度估计运动检测方法 提出一种自适应的核密度(kernel density estimation, KDE)估计运动检测算法. 算法首先提出一种自适应前景、背景阈值的双阈值选择方法, 用于像素分类. 该方法用双阈值能克服用单阈值分类存在的不足, 阈值的选择能自适应进行, 且能适应不同的场景. 在此基础上, 本文提出了基于概率的背景更新模型, 按照像素的概率来更新背景, 并利用帧间差分背景模型和KDE分类结果, 来解决背景更新中的死锁问题, 同时检测背景的突然变化. 实验证明了所提出
kernel
- 解读linux内核源码的入门方法,适合初学-Interpretation of linux kernel source code entry method, suitable for beginners
KPCA
- 为解决PCA不适合多指标综合分析中非线性主成分分析的问题 ,采用核主成分分析 (kpca)方法 ,对我国不同地区 16种腐乳的品质进行了综合评价。 -PCA is not suitable to address the many indicators of a comprehensive analysis of non-linear principal component analysis of the problem, using Kernel Principal Component An
[matlab]
- 模糊核聚类算法的几篇论文及matlab源码，可以以练代学，更好掌握模糊聚类方法。-Fuzzy Kernel Clustering Algorithm matlab several papers and source code, can be practicing on behalf of science, to better grasp the fuzzy clustering method.
KPCAandSVM
- KPCA与SVM共同用于人脸识别 SVM提高了分类效果 KPCA是一种借鉴SVM中核函数的一种较好的特征提取方法-KPCA and SVM for face recognition SVM together to improve the classification results from KPCA is a kernel function in SVM a better feature extraction method
KernelBasedObjectTracking
- A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel.
KDE
- Bivariate Kamma Kernel Density Estimate for large data set-optimize method
kerneladatron
- kernel adatron, svm impelemtation using gradient ascent method, fast and accurate for solving SVM problem with two classes
kerneladatron
- Kernel adatron, solving svm with gradient ascend method. fast and accurate.
Gauss-SVM
- 基于Gauss 核函数SVM分类机，使用二阶几何方法训练。-Gauss kernel function SVM classification based on machine, using the geometric method of second-order training.
SVregression
- In kernel ridge regression we have seen the final solution was not sparse in the variables ® . We will now formulate a regression method that is sparse, i.e. it has the concept of support vectors that determine the solution. The thing to not
Nt-kernel-method
- nt内核函数，包含了常用的nt内核函数名及功能，适合内核及驱动编程人员参考。-nt kernel functions, including a common kernel function name and function of nt, for the kernel and driver programmers reference.
kernel-methods-for-pattern-analysis
- 关于核及模式分析的一些方法,主要包括三个部分-some algorithms on pattern analysis and kernel methods,kernel method for pattern analysis
A-kernel-density-estimate-data
- 一篇核密度估计资料，一种新的核函数选择方法-A kernel density estimate data，A new kernel selection method
Kernel-PCA
- 基于核方法的主成分分析matlab源代码，比较经典，推荐学习。-Method based on kernel principal component analysis matlab source code, more classic, recommended learning.