搜索资源列表
NMF
- 非负矩阵分解的人脸识别NMF 可正常运行 算法源码-Non-negative matrix factorization NMF for face recognition algorithms can be the normal operation of source
code
- 基于非负矩阵分解的语音分离方法，matlab实现-NMF-based speech separation method, matlab implementation
nmf
- 提供NMF程序，非负矩阵分解 用于人脸图像的表示-lnmf and nmf
NMF
- 该软件可实现传统的NMF非负矩阵分解，希望能对大家有所帮助！-This software can realize non-negative matrix factorization. I hope it is helpful for all of us.
100615111[1]..
- 几个简单的计算线性方程系数矩阵分解的算法，包括cholesky、doolittle、等-The calculation of a few simple linear equations coefficient matrix factorization algorithms, including cholesky, doolittle, etc.
nmfpack
- 非负矩阵分解源代码,有经典NMF，LNMF,NMFsc,developped by patrik hoyer-Nonnegative matrix factorization LNMF,NMFsc,developped by patrik hoyer
ogrady2007_phd
- 国外欠定语音盲分离的博士论文，作者为Paul D. O’Grady，LOST算法的作者。该博士论文包括语音信号分离，非负矩阵分解等内容。-Sparse Separation of Under-Determined Speech Mixtures，A dissertation submitted for the degree of Doctor of Philosophy
NoteOnsetDetectionUsingNMF
- 一个音符起点检测程序，其中使用了非负矩阵分解以提取特征减少运算量-NOTE ONSET DETECTION USING NMF
nmfmatlab7
- 非负矩阵分解应用于脸部图像识别的MATLAB程序-function [W H] = nmf(V,r,maxiter)
PIE1
- 基于双权重非负矩阵分解的人脸识别Matlab code-double weight NMF for face recognition
nmf.tar
- 非负矩阵分解程序，里面包含了全面的相关资料和程序代码。-Non-negative matrix factorization program
DISCRIMINANTSPARSENONNEGATIVEMATRIXFACTORIZATION.r
- 判别稀疏非负矩阵分解，提出这个新算法，来进行人脸识别，比传统的NMF和一些其他的扩展算法效果好-Sparse non-negative matrix factorization judge proposed the new algorithm for face recognition, than the traditional extension of NMF algorithm and some other good results
Nonnegative_matrix_factorization.tar
- Nonnegative_matrix_factorization是实现非负矩阵分解的程序，该算法可以用来进行图像分解和模式识别 -Nonnegative_matrix_factorization is to achieve non-negative matrix factorization procedure, the algorithm can be used for pattern recognition and image decomposition
非负矩阵分解
- 盲信号分离中的非负矩阵分解，高光谱图像解混等等。
nmf
- 非负矩阵分解，处理合成孔径雷达图像，数据处理(The multichannel or wide-angle imaging performance of synthetic aperture radar (SAR) can be improved by applying the compressed sensing (CS) theory to each channel or sub-aperture image formation independently.)
编程实践题目-矩阵分解
- 一、穆勒矩阵构成 穆勒矩阵是一个4*4的矩阵，完整描述了介质的偏振属性。可通过水平线偏振光H、垂直线偏振光V，45°线偏振光P，右旋圆偏振光R入射，并分别探测水平线偏振光H、垂直线偏振光V，45°线偏振光P，右旋圆偏振光R出射情况下的能量值，即16种偏振态组合下的强度结果，HH/ HV/ HP/ HR，PH/ PV/ PP/ PR，VH/ VV/ VP / VR和RH/ RV/ RP/ RR。进而Mueller矩阵可按照公式（1）计算得到：(First, the Muller matrix
NMF
- 用于非负矩阵分解的程序，包含C程序、MATLAB程序(NMF algorithm % Check that we have non-negative data)
NMF
- 实现非负矩阵分解的程序，适合提取非负信号的特征值(A program for non negative matrix factorization, Suitable for extracting the eigenvalues of non negative signals)
非负矩阵分解
- 实现高光谱图像的非负矩阵分解，可以在此基础上添加优化算法，实现更高精度和速度。(To achieve hyperspectral image's non negative matrix factorization, we can add optimization algorithm to achieve higher accuracy and speed.)
新建文件夹
- 非负矩阵分解的matlab代码，适合新手利用matlab学习非负矩阵分解(Matlab code for nonnegative matrix decomposition)