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stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
kernel_pca
- Kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with
Kernel_PCA
- 基于核的主分量分析方法的提出者亲自写的程序（基于MATLAB-a MATLAB m-file of Kernel PCA
KPCA
- 在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验. -Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and reco
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.
PCA
- 基于PCA的人脸识别 Matlab代码 两种方法 KL 和kernel-PCA-based face recognition Matlab code
kernelPCA
- kernel PCA MATLAB code
kPCA_v3.1
- Computation of Kernel PCA
function_kpca
- 使用核函数，在matlab环境下实现非线性主成分分析(Using kernel function to realize nonlinear principal component analysis in Matlab environment.)