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keigen
- 使用PCA抽取人脸灰度图片的前k个特征向量，计算人脸灰度图片的散布矩阵并且抽取其前k个作为主特征-using PCA to extracte gray picture face of the first k eigenvectors to calculate gray-scale image of the face spreading matrix, and taking its pre-k-as the main characteristics
PCA
- This programme is to calculate the principal component analysis (PCA) of a image. Naturally it is used to reduce the dmentionality of the image.
Matlabcodes-RobustPCA
- Matlab codes for Robust PCA multivariate control chart-Robust PCA multivariate control chart mainly consists two steps: Step1 Calculates the robust mean and the robust covariance of original dataset using the minimum covariance determinant (M
featureface
- 利用matlab编程pca和fld算法来计算人的特征脸-Programming using matlab pca and fld algorithm to calculate the characteristics of human face
pca
- PCA技术的一大好处是对数据进行降维的处理。我们可以对新求出的“主元”向量的重要性进行排序，根据需要取前面最重要的部分，将后面的维数省去，可以达到降维从而简化模型或是对数据进行压缩的效果。同时最大程度的保持了原有数据的信息。-A major advantage of PCA technology is reduce the dimension of the data processing. We can calculate the new " principal component&qu
PCA
- 应用STC单片机的PCA功能测量经测速装置输出的PWM方波的脉冲宽度，从而计算出速度，并用串口将速度数据发到计算机。-SCM application PCA STC function measurement device by the speed of the PWM square wave output pulse width to calculate the speed and the speed with a serial port data to the computer.
Face-recognition-using-pca
- 使用主成分分析进行人脸图像的识别，并计算识别率-Using principal component analysis for face image recognition, and calculate the recognition rate
PCA
- 带有数据的PCA程序，计算方差贡献率确定主元数，有T方和SPE图-PCA program with data, calculate the variance contribution rate to determine the number of principal, with a T square and SPE chart
picPCA
- This function used to calculate PCA of image.
PCA-renlianshibie
- 采用PCA提取人脸特征,先计算M个图像的平均值脸，再求出各特征值脸。-Using PCA for face feature extraction, first calculate the average face image of M, and then find the face value of each characteristic.
Image PCA
- This function used to calculate PCA of image.
PCA
- 该代码通过下载txt文件里的数据或读入图片，可以计算出该矩阵的相关系数矩阵的特征根和特征向量。-The code txt file by downloading data or read into the picture, you can calculate the characteristic roots and eigenvectors of the correlation matrix of the matrix.
pca
- 人脸识别，输入200副人脸照片作为训练集，检测另外200副人脸图像，计算错误率。-Recognition, input 200 people face photo as the training set, testing additional 200 people face image to calculate the error rate.
pca
- princa，用于pca主成分降维：计算第k主成份贡献率-累计贡献率-取累计贡献率大于等于90%的主成分(For PCA principal component dimensionality reduction: calculate the principal component contribution rate of K - the cumulative contribution rate - take the cumulative contribution rate greater tha
PCA
- Python实现PCA将数据转化成前K个主成分的伪码大致如下: ''' 减去平均数计算协方差矩阵计算协方差矩阵的特征值和特征向量将特征值从大到小排序保留最大的K个特征(Python PCA data into pseudo code before the K principal components are as follows: the characteristics of 'average minus the covariance matrix to calculate the covari
MNIST-PCA
- 使用PCA算法分析MNIST 手写字符训练样本。 结果分别生成以2、5、10个PCA主成分的重构图像以及10个主成分特征向量的对应图像。(Implement PCA algorithm on MNIST dataset and calculate the class PCA on each digit separately.)
PCA
- 1、读入图片，根据PGN格式的line 2 确定矩阵的大小为 28*28=784，根据line4 获取. 2、读入图片，根据PGN格式的line 2 确定矩阵的大小为 28*28=784，根据line4 获取。 3、计算平均矩阵。 4、对平均值矩阵进行SVD： 5、平均矩阵进行SVD后的前20个singular vector的输出结果。 6. 将训练集的每一张图片当成一行，形成一个矩阵，然后对矩阵进行PCA分解。 7. 这个矩阵对测试集的每张图片进行降 维，得到的图像。(1, rea
PLSPCAT2andspe
- 故障检测，分别是pls和pca，计算spe和t2控制量。(Fault detection is pls and PCA, respectively, to calculate SPE and T2 control.)
PCA
- 使用matlab自带的函数princomp()计算主成分，当维数很高时通常会出现内存耗尽的错误，即使内存足够也非常耗时。快速pca能加快计算进程且减小内存占用，更容易计算较大尺寸的图像主成分。(Use MATLAB's own function princomp () to calculate the principal component. When the dimension is very high, the memory exhaustion error usually occurs,
chapt 2
- 使用MPCA进行故障检测，以按批次和变量方向分别展开数据，计算T2和SPE统计量。(MPCA is used for fault detection to expand data according to batch and variable directions, and to calculate T2 and SPE statistics.)