搜索资源列表
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,
KPCA.zip
- kPCA程序 一个关于kernel pca的实现代码,kpca
Kernel-PCA
- KPCA经典程序，是KPCA的创始人写的，为学习KPCA提供了模板。-Classic KPCA procedures, is the founder of KPCA wrote, KPCA provides templates for learning.
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
kpca
- 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
KPCA
- kernel PCA
pcajiafisher
- pca+fisher是将核函数应用到人脸识别研究中去-pca+ fisher is the kernel function is applied to face recognition research go
kpca_toy
- Kernel PCA的经典示例程序，非常有帮助，也很易懂。-Kernel PCA classic example of the procedure
palmprint
- Palmprint Recognition by Applying Wavelet-Based Kernel PCA
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
sch99kernel
- This pdf file of Kernel PCA-This is pdf file of Kernel PCA
kpca_origin
- Kernel PCA toy example Nonlinear component analysis as a kernel Eigenvalue problem
26
- 关于rbf神经网络实现图像分类的优化算法英文文献 源于著名期刊I-A METHOD FOR IMAGE CLASSIFICATION BASED ON KERNEL PCA
KECA
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010. We introduce kernel entropy component analysis (kernel ECA) as a new method
gradient_descent_opt
- --- --- --- --- ---Kernel PCA --- --- --- --- - kpca1 | Simple Example of Kernel PCA on a artificial datasets | kpca2 | Example of KPCA. this is a B.Scholkopf modified routine | kpca3 | Example of Multilayer SVM with a KPCA as a fir
face-recog-using-kernel-pca
- face recognition using PCA
KERNEL-PCA
- Kernel principal component analysis (kernel PCA) 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 a n
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.
Kernel PCA and Pre-Image Reconstruction
- Kernel Pca for face recogntion
PCA-ICA
- 实现了主元分析（PCA）和独立分量分析（ICA）相关信号处理。非线性降维。(Implements Principal Component Analysis (PCA) and Independent Component Analysis (ICA) correlation signal. Non-linear dimension reduction using kernel PCA.)