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主分量分析的MATLAB程序，对于初学者比较有用，可以好好看一下-MATLAB program, the principal component analysis is useful for beginners, you can take a look at
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在多变量统计中，数据有很强的相关性，对数据进行主成分分析，这样可以避免过拟合- Multivariate statistical data there is a strong correlation, principal component analysis of the data, and to avoid over-fitting
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此程序解释了主成分分析PCA的用法通过matlab将其实现-This program explains the principal component analysis PCA usage by matlab to achieve
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principal component analysis(PCA)主成分分析，Matlab实例代码-principal component analysis(PCA)
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经典主成分分析法，实现高光谱图像的降维处理 -Classical principal component analysis, to achieve high spectral image dimensionality reduction
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为有效解决局部二元模式(LBP)在人脸识别特征提取时维数过高的问题，提出了一种结合LBP特征和主成分分析(PCA)的人脸识别方法．-To effectively solve the local binary pattern (LBP) feature extraction in face recognition problem of high dimensionality, we propose a combination of LBP features and principal compon
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基于主成分分析的人脸特征提取的MATLAB源代码，通过测试的-Principal component analysis based on human face feature extraction MATLAB source code, pass the test
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主成分分析算法，很经典的编写matlab的方式，极其类似系统函数-Principal component analysis algorithm, very classic written in MATLAB, very similar to the system function
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this principle component analysis(PCA) that is used for linear dimensionality reduction and feature extraction as well as the nonlinear form of PCA which is KPCA and how PCA is used for Active shape models -this is principle component analysis(PCA) t
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主成分分析，用于对数据进行主要因素分析，便于求出主要数据对系统的印象-Principal component analysis
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近红外光谱主成分分析，适用于各类光谱定性和定量计算使用-Near Infrared Spectroscopy principal component analysis, applicable to all types of spectrum use qualitative and quantitative calculation
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主成分分析（Principal Component Analysis，PCA）， 将多个变量通过线性变换以选出较少个数重要变量的一种多元统计分析方法-Principal Component Analysis，PCA
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自己编写的PCA主成分分析法，希望能够帮助大家-I have written the PCA principal component analysis method, hoping to help everyone
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PCA主元分析法求主元个数，Q和T2的源程序-PCA principal component analysis method for the number of main elements, Q and T2 of the source
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是学习PCA特征提取的很好的学习资料，主同步信号PSS在时域上的相关仿真，多元数据分析的主分量分析投影。- Is a good learning materials to learn PCA feature extraction, PSS primary synchronization signal in the time domain simulation related, Principal component analysis of multivariate data analysis p
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正确率可以达到98％，借鉴了主成分分析算法（PCA），最大似然（ML）准则和最大后验概率（MAP）准则。- Accuracy can reach 98 , It draws on principal component analysis algorithm (PCA), Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion.
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是一种双隐层反向传播神经网络，借鉴了主成分分析算法（PCA），包括面积、周长、矩形度、伸长度。- Is a two hidden layer back propagation neural network, It draws on principal component analysis algorithm (PCA), Including the area, perimeter, rectangular, elongation.
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IMC-PID是利用内模控制原理来对PID参数进行计算，分析了该信号的时域、频域、倒谱，循环谱等,借鉴了主成分分析算法（PCA）。- The IMC- PID is using the internal model control principle for PID parameters is calculated, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. It d
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pca 主成分分析的matlab代码。主成分分析（Principal Component Analysis，PCA）， 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量，转换后的这组变量叫主成分。(PCA principal component analysis matlab code. Principal component analysis (Principal Component, Analysis, PCA) is a statistical method
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