搜索资源列表
sime-kpca
- 基于半监督的核主元分析matlab代码，基于半监督核主元分析matlab代码-Based on the semi-supervised KPCA Matlab code, Based on the semi-supervised KPCA Matlab code
KStattoolbox KPCA工具箱
- 这是一个kpca的工具箱，用于kpca的使用
kpca.rar
- 一个利用KPCA进行故障诊断的程序，用起来很简单，里面有详细的标注,A use of KPCA for fault diagnosis procedure is very simple to use, which has detailed tagging
kpca
- 核主成分分析算法KPCA 的matlab程序/代码 基于二维数据的。-kernel principal component analysis
kpca_azaaza
- kpca 基于核主成分分析的源程序，有注释，希望对大家有帮助！-kpca based on kernel principal component analysis, source code, there are comments, want to help you!
drtoolbox
- 降维工具箱，包含主元分析（PCA）,核主元分析（KPCA）等。-Dimensionality reduction kit, including principal component analysis (PCA), Kernel Principal Component Analysis (KPCA) and so on.
kpca
- KPCA降维算法的实现函数，matlab的函数-KPCA dimensionality reduction algorithm to achieve the function, matlab function
kpca
- 一种加核的PCA算法，比PCA算法识别率高很多，所加的核可以用于其他算法。-An increase in the PCA algorithm for nuclear than the PCA algorithm is much higher recognition rate, the increase of other algorithms can be used for nuclear.
KPCA
- Kernel Principal Component Analysis
kpca1
- kpca核主成分分析用于故障诊断与辨识中，具有很强的应用价值-kpca kernel principal component analysis for fault diagnosis and identification, has a strong value
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
KPCA
- matlab 源码 KPCA/核PCA 可用于人脸识别-matlab source KPCA/nuclear PCA for Face Recognition
kpca
- 运用KPCA方法在ORL人脸库上进行人脸识别，分类器为最近邻分类器。-KPCA method using ORL face database for face recognition, classification for the nearest neighbor classifier.
KPCA
- KPCA主要在图像去噪声方面有应用。此外还可以进行特征提取，降维使用.-KPCA major noise in the image to have the application. You can also feature extraction using dimension reduction.
kpca
- KPCA的matlab代码，经过验证，可以用的代码-matlab code for KPCA,it can be used
KPCA故障检测程序（代码已优化）
- 基于核主元分析（KPCA）的工业过程故障检测，代码已优化，运行效率高，有详细的注释，附有训练数据和测试数据。(Achieves fault detection of industrial processes based on Kernel Principal Component Analysis (KPCA); the code has been optimized for high operational efficiency; detailed notes are attached with
KPCA实现
- 有一个讲解kpca的个PPT，和一个用MATLAB实现的kpca的程序(There is a PPT explaining KPCA and a KPCA program implemented by MATLAB.)
KPCA
- KPCA算法属于非线性高维数据集降维，算法其实很简单，数据在低维度空间不是线性可分的，但是在高维度空间就可以变成线性可分的了(The KPCA algorithm belongs to the nonlinear high-dimensional data set dimension reduction. The algorithm is very simple. The data is not linearly separable in the low-dimensional space, b
核函数主成分分析KPCA
- 在多元统计领域中，核函数主成分分析(kernel principal component analysis, kernel PCA)是利用核函数方法技术对主成分分析(PCA)的扩展。使用核函数使原PCA的线性操作是在一个复制的内核希尔伯特空间中执行的。 KPCA的运算步骤势在PCA之前首先对数据进行kernel变换 ，再求相关系数矩阵。(In the field of multivariate statistics, kernel principal component analysis (ke
KPCA-故障检测
- 内附有对应的数据集，直接测试即可。利用KPCA进行降维。(With data sets, direct testing is enough.)