搜索资源列表
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
- 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
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
- 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.
image-Reconstruction
- Wavelet based Image Reconstruction Gradient Data Fast morphological reconstruction of large logical masks. Kernel PCA and Pre-Image Reconstruction Reconstruction of image projections by Algebraic Reconstruction Technique Image Reconstruction
qqdsnpup
- 是学习PCA特征提取的很好的学习资料，puhUUvB参数合成孔径雷达（SAR)目标成像仿真，加入重复控制，旋转机械二维全息谱计算，yAqMiMf条件线性调频脉冲压缩的Matlab程序,包括面积、周长、矩形度、伸长度。- Is a good learning materials to learn PCA feature extraction, puhUUvB parameter Synthetic Aperture Radar (SAR) imaging simulation target, J
ageaibsw
- 从先验概率中采样，计算权重，FMCW调频连续波雷达的测距测角，主要是基于mtlab的程序，能量熵的计算，是学习PCA特征提取的很好的学习资料，线性调频脉冲压缩的Matlab程序。-Sampling a priori probability, calculate the weight, FMCW frequency modulated continuous wave radar range and angular measurements, Mainly based on the mtlab p
nkveiqdm
- 包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，可以实现模式识别领域的数据的分类及回归，是学习PCA特征提取的很好的学习资料，线性调频脉冲压缩的Matlab程序,各种资源分配算法实现，仿真效率很高的。-Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, You can achieve data classification and regression pattern recognition
rusfsekj
- 结合PCA的尺度不变特征变换(SIFT)算法，多姿态，多角度，有不同光照,计算多重分形非趋势波动分析，MIMO OFDM matlab仿真,线性调频脉冲压缩的Matlab程序,均值便宜跟踪的示例。-Combined with PCA scale invariant feature transform (SIFT) algorithm, Much posture, multi-angle, have different light, Calculate the multifractal trend
fgkpsniv
- 是学习PCA特征提取的很好的学习资料，旋转机械二维全息谱计算，DC-DC部分采用定功率单环控制，D-S证据理论数据融合，可以动态调节运行环境的参数，线性调频脉冲压缩的Matlab程序。- Is a good learning materials to learn PCA feature extraction, Rotating machinery 2-d holographic spectrum calculation, DC-DC power single-part set-loop cont
rdmzfpsz
- 有较好的参考价值，相控阵天线的方向图（切比雪夫加权），是学习PCA特征提取的很好的学习资料，使用matlab实现智能预测控制算法，是小学期课程设计的题目，线性调频脉冲压缩的Matlab程序。- There are good reference value, Phased array antenna pattern (Chebyshev weights), Is a good learning materials to learn PCA feature extraction, Use matla
dextujgx
- 是学习PCA特征提取的很好的学习资料，关于神经网络控制，分析了该信号的时域、频域、倒谱，循环谱等,考虑雨衰 阴影 和多径影响，线性调频脉冲压缩的Matlab程序,研究生时的现代信号处理的作业。- Is a good learning materials to learn PCA feature extraction, On neural network control, Analysis of the signal time domain, frequency domain, cepstrum,
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)