搜索资源列表
FN-KNN
- 基于k近邻规则的PCA方法，改进的主元分析法用于故障诊断-PCA based on KNN
VRE-PCA
- 关于主元分析选取方法重构误差方差法（VRE）的MATLAB仿真代码。-About PCA reconstruction error variance method selection method (VRE) MATLAB simulation code.
pca
- 关于主元分析的简单的小程序。适用于初学者。-Simple program about PCA. Suitable for beginners.
kpca
- 核主元分析程序,基于主元分析进行开发编写，可实现核空间数据降维-KPCA program developed to prepare based on principal component analysis, nuclear spatial data dimensionality reduction
KPCA
- KPCA（核主元分析法）基于MATLAB平台的核主元分析法-KPCA (kernel principal component analysis)
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- 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 (PCA) is based fault diagnosis technique multivariate statistical process control at the core of the current,
1
- MATLAB PCA 基于主元分析的柴油机故障检测程序-MATLAB PCA
PCA
- 主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题-Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical analysis of the principal contradiction of things to ma
06102001
- 基于主元分析法的数据降维研究，Matlab实现-Based on principal component analysis method of data dimension reduction research, Matlab
PCA
- 主元分析算法的matlab实现，可实现数据降温处理，模块完整，可直接应用。-Principal component analysis
newPCA
- 一种新的主元分析降维方法，PCA特征矩阵与相关系数法相结合，结合系数通过归一化方法求出同时满足贡献率与相关性分析的特征变量-a new strategy of PCA dimensionality reduction .the combination of PCA with Correlation coefficient，Feature variable is adappted to Correlation coefficient analysis and contribution rate
pca
- 主元分析java源代码，很好的学习资料 值的一看-PCA java source code, good learning materials
pca
- 基于主元分析的异常检测和故障诊断，用于对具有高度线性相关的测量数据进行分析和处理，其最终实现高维空间降维的目的。-Anomaly detection based on principal component analysis and fault diagnosis, used for highly linear correlation measurement data analysis and processing, its ultimate achieve the goal of higher
pcaPmatlab
- 主元分析和核主元分析MATLAB程序及讲义 -PCA Principal component analysis and principal component analysis of MATLAB and the worksheets
PcaBR
- 主元分析方法和用最优重构法确定最佳主元数。-Principal Component Analysis and determine the optimal number of PCA with best reconstruction method(BR).
KICA
- 核独立主元分析(KICA算法)在模式识别、过程监测、故障诊断等不同领域的应用中都表现了很好的性能。-Kernel independent principal component analysis (KICA algorithm) has shown good performance in pattern recognition, process monitoring, fault diagnosis and other fields.
Kpca
- 核主元分析法，将低维数据，映射到高维空间，进行更精确的非线性划分。-Kernel principal component analysis, the low-dimensional data, mapping to high-dimensional space for more accurate non-linear division.
PCAMatlab
- PCA主元分析及实现方法(内含《精通MATLAB数字图像处理与识别》)-Analysis of PCA Principal Component and Its Implementation
77257795PCA_yuandaima
- PCA源程序，主元分析源程序，可以用于变量的特征提取(PCA source code, principal component analysis source, can be used for variable feature extraction)
PCA
- MATLAB实现主元分析法，实现数据的压缩，提取主元(MATLAB realize Principal Component Analysis, To achieve data compression, extract the principal component)