搜索资源列表
PCA
- 用来进行主成分分析，实现数据压缩功能，也可以做特征提取与分类-Be used for principal component analysis, data compression, you can also do feature extraction and classification
image-compression-with-PCA
- 对400幅灰度图像用分块PCA的方法进行压缩，进行通信时只用传输主元和特征向量。其中，pcaxiefangcha.m用于图像压缩，imresume.m用于图像恢复和部分图像的显示，chaweight.m用于绘制特征值比重-主元个数关系图，crdraw.m用于绘制压缩比-主元个数关系图，psnrdraw.m用于绘制总误差PSNR-主元个数关系图，psnrlocation.m用于绘制单幅图像误差PSNR分布图。-On the 400 block with a gray image compressi
pca_img_compress.tar
- matlab 用PCA方法对图像进行压缩、还原-PCA method using matlab image compression, restore
facedetection
- PCA、LDA人脸检测，压缩包里实现了PCA、LDA、最小距离分类器，人脸检测！-PCA, LDA face detection, compression bag to achieve the PCA, LDA, minimum distance classifier, face detection!
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
mcmc
- 这是一个基本的PCA方法实现人脸图像压缩与重建，可以非常快捷的将一些无法辨别的人脸图像进行快速的拼接。-This is a basic PCA method to achieve image compression and reconstruction of the face, can be very quick to identify the human face that can not be quickly spliced images.
PCA_neural_networks
- PCA for image compression, Sanger s algorithm implemented with neural networks
Copy-Detection
- 使用下采样帧构成的列向量的PCA系数作为每帧特征（原则上，也可以使用其他类型的关键帧特征），多帧特征构成特征矢量，以高斯概率模型的后验概率衡量相似性、并建立k维树结构的索引进行搜索，文中对噪声、模糊、再压缩、加Logo，及其这些变换的两两组合进行了实验（丢帧很少时也可以），速度很快，适合于大规模因特网视频的搜索。-Use sampling frame column vector of the PCA coefficients as each frame features (in principl
new-pca
- 这是个改进的PCA主元分析程序 可以实现数据降维和压缩-This is a PCA improved principal component analysis program can reduce the dimensionality of data compression
PCA
- 主成分分析(Principal Component Analysis, 简称PCA)是一种常用的基于变量协方差矩阵对信息进行处理、压缩和抽提的有效方法。 -The principal component analysis (Principal Component Analysis, PCA) is a common covariance matrix of information processing, compression and extraction.
2DduplexingPCA(2D2PCA)
- 2D双向PCA(2D2PCA),二维主成分分析(2DPCA)的实质是对图像矩阵按行进行图像压缩抽取特征,消除了图像列的相关性.-2D bidirectional PCA (2D2PCA), two-dimensional principal component analysis (2DPCA) real image matrix row the Image Compression extraction characteristics to eliminate the correlation of
pca
- 基于主成分分析方法即pca法的数据压缩与解压缩代码-Method that is based on principal component analysis pca method data compression and decompression code
pca
- 用PCA算法在matlab平台上对图像进行压缩与解压缩，内含测试图像，能直接在matlab上运行使用，对学习PCA算法有帮助。-PCA algorithm used in matlab platform for image compression and decompression, containing the test images, can be run directly on matlab, PCA algorithm is helpful for learning.
denoised_image_PCA
- 自适应PCA 用于信号处理中，在图像压缩，图像识别方面也很有帮助，很有用的代码-, Image compression, image recognition is also very helpful, very useful code for adaptive signal processing in PCA
pca
- PCA主成分分析，是一种常用的基于变量协方差矩 阵对信息进行处理、压缩和抽提的有效方 法。 -PCA principal component analysis, is a common and effective method is based on the covariance matrix of variable information processing, compression and extracted.
PCA_Gaus_Iris
- Compression by PCA of Gaussian and Iris data
PCA
- 双谱分析获取信号成分，PCA获取信号主成分，剔除无用成分-PCA extracted bispectrum principal component, data compression, signal acquisition signal independent components, principal component.
pca
- 应用主成分分析将数十维数据压缩，得到主成分，根据主成分得分给案例排序，得到案例 的得分排序，从而得到评价结果。-Principal component analysis of dozens dimensional data compression, get the main ingredients, according to the principal component scores to sort the case to give the case to score the sort to
Matlab file
- PCA实现图像压缩 matlab代码，根据pca选出累计概率达到90%的特征，作为新的特征，并根据新的特征实现图像的重建(PCA implementation of image compression Matlab code)
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)