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drtoolbox.tar
- 这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值- ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techn
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
Kernel-PCA
- calculation algorithm for principle component analysis based kernel of any image database.
Two_D_KPCA
- 2维核PCA算法，应用于人脸识别等图形图像处理中。-2 dimensional kernel PCA algorithm, can be applied to graphics such as face recognition in image processing.
kpca_py
- python实现的PCA，即Python scr ipt for kernel PCA with and without CUDA,效率非常好-python implementation of the PCA, Python the scr ipt for kernel the PCA with and without CUDA, the efficiency is very good
13FaceRec
- 人脸特征提取与识别matlab程序，主要提取了PCA特征、SVM分类和核方法分类等，代码可以直接使用-Face recognition based on PCA features and Kernel methods, which is used in pattern extraction.
PCA-SVM
- 本程序使用MATLAAB R2014a 编写，基于PCA_SVM的人脸识别程序。程序包括主成份分析、SVM核函数，并附带了人脸库，使之能够直接调用人脸库图像进行人脸识别-The program uses MATLAAB R2014a written procedure based on recognition of PCA_SVM. Program includes principal component analysis, SVM kernel function, and comes face
KPCA
- 核主成分分析KPCA算法，经过核变换将样本映射到线性可分的高维空间，再进行PCA降维。包括训练、测试、识别整个过程-KPCA kernel principal component analysis algorithm through nuclear transformation samples are mapped to linearly separable high-dimensional space, then PCA dimensionality reduction. Including