搜索资源列表
PCAKPCA
- PCA和KPCA程序，matlab实现，可用于模式识别时做降维或特征提取处理-PCA and KPCA program, matlab implementation, pattern recognition can be used to do when dealing with dimensionality reduction or feature extraction
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.
KStattoolbox
- 这个是KPCA的matlab工具包，台湾的一个大学开发，能够实现KPCA的基本功能-This is a matlab toolkit KPCA, Taiwan, a university development, to achieve the basic functions of KPCA
4
- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十六-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
PCA-method-for-fault-diagnosis-routine-five(includ
- 用于故障诊断的PCA方法例程5个(含KPCA)，利用PCA（主元分析）方法或者KPCA方法，进行工业系统的故障诊断程序，有详细的注释说明-PCA method for fault diagnosis routine five (including KPCA), using PCA (principal component analysis) method or KPCA method, industrial process fault diagnosis, a detailed explanat
KLPP
- 核lpp（局部保持映射）的降维方法。跟Xiaofei He的论文配套-Nuclear lpp (partial maintain mapping) methods of dimensionality reduction. Xiaofei He told the paper supporting
LDA2D-2
- 人脸识别中2DLDA算法的matlab程序，使用最近邻分类器进行识别。-Face Recognition 2DLDA algorithm matlab procedures, the use of nearest neighbor classifier to identify.
KPCA_SVM_Train
- 核主元分析和支持向量机结合的故障诊断方法-KPCA and SVM fault diagnosis method combining
BasedonprincipalcomponentanalysisoftheFaceRecognit
- 在特征提取阶段，研究了PCA, 2DPCA, (2D) 2PCA, DiagPCA, DiagPCA-F-2DPCA等多 种方法。不同于基于图象向量的PCA特征提取，由于2DPCA, (2D) ZPCA, DiagPCA和 DiagPCA-I-2DPCA的特征提取都直接基于图象矩阵，计算量小，所以特征的提取速度明 显高于PCA方法。-In the feature extraction stage, the study of the PCA, 2DPCA, (2D) 2PCA,
3inputvector1
- 是基于主成成分和核主成成分的实例，有详细的注解，条理清晰易懂，适合初学者对pca与kpca的学习。-Is based on the principal as the main components and nuclear components as examples of the comments in detail, the clarity of easy-to-understand for beginners and pca learning kpca.
cwstd
- 是基于主成成分和核主成成分的实例，有详细的注解，条理清晰易懂，适合初学者对pca与kpca的学习。-Is based on the principal as the main components and nuclear components as examples of the comments in detail, the clarity of easy-to-understand for beginners and pca learning kpca.
KPCAandSVMbasedonstaterecognitionoftheDieselEngine
- 基于KPCA_SVM的柴油机状态识别方法的研究 把KPCA与SVM共同用到柴油机状态识别中-KPCA_SVM based on the state of the diesel engine study to identify methods of KPCA and SVM to identify the common use of diesel engine state
PSO-SVMface
- 基于PSO训练SVM的人脸识别 利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径-PSO-based SVM for face recognition training using support vector machine learning ability in the performance of good performance, combined with KPCA
KPCA_p
- 核主成分分析中使用多项式核函数时的MATLAB代码，有注释，易看懂。-Kernel Principal Component Analysis in the use of polynomial kernel function of the MATLAB code, annotated, easy read.
denoise_kpca
- 去噪基于kPCA方法，欢迎使用。使用matlab编程-De-noising method based on kPCA are welcome to use. Programming using matlab
KPCA_vs_PCA
- 原创的基于Matlab 的kpca 源程序，大家一起学习一下-Matlab-based kpca original source, everyone works together to learn about
KDA_Plus_KPCA_for_Face_Recognition
- KDA Plus KPCA for Face Recognition.pdf
backfitting
- 核主成分分析方法 可将低维空间数据转至高位空间的内积，再转至源空间-Kpca can be low to high dimension space data within the space of deposition, turn again to the source of space
pcakpca
- 图像降维方法pca和kpca的matlab程序-Image dimensional reduction pca and kpca the matlab program
PCAexample
- 核主元分析的程序，很好用，希望大家喜欢-KPCA procedure very well with the hope that you like! !