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kpca
- KPCA实现数据压缩，所用核函数为高斯核函数-KPCA to achieve data compression, used in nuclear function for Gaussian kernel function
kpcaprogram
- 核主元分析程序，本人毕业设计程序，用于降维，监测Te过程故障，误诊断率低。-KPCA program, I graduated from the design process for dimension reduction, monitoring Te process failure, error diagnosis rate is low.
pca-kpca
- kca & kpca matlab 源程序 需要的可以-kca & kpca matlab source code need to take a look at
dfadgae
- 本程序为KPCA对于过程监控的算法，有很好的监控效果，欢迎您下载 -The procedure for the KPCA algorithm for process monitoring, the monitoring results are good, you are welcome to download
kkpcca11p
- 关于kpca算法的matlabb程序源码及其说明 -On kpca algorithm the matlabb program source code and its descr iption
KPCA
- 本方法使用sprtool，介绍了Kpca的应用，来进行高位数据降维，介绍三种核函数的应用，并附有结果图。-This method uses sprtool, introduced Kpca applications for high data dimensionality reduction, introduced three nuclear function, together with the results in Fig.
kpca
- 这是一段核主元分析算法的源程序，仅供参考-This is a kernel principal component analysis algorithm source code, for reference only
KPCA
- KPCA 介绍核PCAdehanshumokuai -matlab KPCA
KPCA
- 核主成分分析是一种流行的非线性特征提取方法- Kernel principal component analysis is a popular nonlinear feature extraction method
kpca
- 核主成分分析方法是主成分分析的改进算法，其采用非线性方法提取主成分-Kernel principal component analysis method is an improved algorithm of principal component analysis, which uses a nonlinear principal components extracted
kpca
- 主元分析法(PCA)是目前基于多元统计过程控制的故障诊断技术的核心，是基于原始数据空间，通过构造一组新的潜隐变量来降低原始数据空间的维数，再从新的映射空间抽取主要变化信息，提取统计特征，从而构成对原始数据空间特性的理解。-Principal Component Analysis
KPCA
- 核主分量分析程序，有简单的代码。易学，分享给大家。-Kernel principal component analysis procedure, a simple code. Learn and share with everyone.
kpca
- 此kpca代码，是自己手动编写的线性代码，有什么不对的地方，多多交流。-This kpca code is to manually write linear code, what is wrong with it, more exchanges.
KPCA
- 这是一个关于核主元分析的代码,在win7平台上用C++编写-This is the code on nuclear Principal Component Analysis on win7 platform written C++
PCA-KPCA
- 关于数据降维PCA和KPCA的MATLAB程序，程序完整，可以直接运行-PCA and KPCA
KPCA
- 基于KPCA的故障检测，包里包含了测试数据和训练数据，可以直接运行(Based on KPCA fault detection, the package contains test data and training data that can be run directly)
KPCAomit
- 使用kpca方法进行特征提取，用作机器学习的第一步(Use kpca method for feature extraction, as the first step in machine learning)
kPCA_v3.1 (1)
- KPCA用于数据特征的降维，先通过核方法，将样本映射到高维空间，再进行主成分分析过程。(KPCA is used to reduce the dimension of data, first through the kernel method, the sample is mapped to high-dimensional space, and then the principal component analysis process.)
kpca
- 实现工业系统过程中的故障诊断，以及进行有效的检测，从而发现故障问题(Implement fault diagnosis and detection)
PCA,KPCA完整程序
- 降维，用作聚类算法使用。具有很好效果，可以用作图像去噪(Dimensionality reduction is used as a clustering algorithm. It has good effect and can be used for image denoising.)