搜索资源列表
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!
KPCAEXAMPLE
- 一个很好的核主成分分析matlab程序应用举例。该程序是在前人的核主成分分析程序基础上做了适当的修改产生的，可用于多维数据的降维和压缩处理。-A good kernel principal component analysis matlab application procedures, for example. The program is in the predecessors of Kernel Principal Component Analysis based on the proce
CKPCA-HOG-SVM
- 为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
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.
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.
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
svm
- svm核主成分分析，简单实用，毕业论文程序-svm kernel principal component analysis, simple and practical, graduation procedures
imagefeatureextractionmethod
- 桌红外图像特征提取方法研究。基于模糊核主成分分析的高光谱遥感影像特征提取研究。-Table infrared image feature extraction method.
kpca
- 基于聚类分析的核主成分分析，简单实用，希望对大家有帮助。-Based on cluster analysis of kernel principal component analysis, simple and practical, we want to help.
KPCA_SVM
- 核主成分分析和支持向量机方法相结合，用于数据分类和预测。-Kernel principal component analysis and support vector machine method combined for data classification and prediction.
kpca
- 核主成分分析，用于轴承故障，人面识别，水位分布等的数据非线性提取。-Kernel principal component analysis for data bearing failure, human face recognition, water distribution and other non-linear extraction.
kpca
- 上传的这个Matlab源代码可以用于主成分分析以及核主成分分析，学者们可以通过此方法实现数据的压缩。-this can be used to have a Principal component analysis and a Kernel Principal component analysis by those research works
KPCAmatlab
- 核主成分分析方法kpca在matlab中的实现，包含参数优化等-KPCA in matlab
KPCA
- 根据自己对于核主成分分析算法的理解，编程实现的MATLAB程序，如有理解不到位的地方，欢迎批评指正。-According to their own understanding of the analysis program MATLAB algorithms, programming for nuclear principal component, if understood not in place, welcome criticism.
核主成分分析
- 在具有降维作用的核主成分分析方法基础上增加一个核函数成为新的核主成分分析方法。(On the basis of kernel principal component analysis with dimension reduction, a kernel function is added to be a new kernel principal component analysis method.)
KPCA
- 核主成分分析方法，过程非常详细，可用于分类和降维(The kernel principal component analysis method is very detailed and can be used for classification and dimensionality reduction)
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.)
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
LLTSA降维
- 这个是KPCA核主成分分析的代码，好用，里面也带有范例(This is the KPCA kernel principal component analysis code, which is easy to use and also contains examples.)