搜索资源列表
l1_ls
- 基于最小二乘思想解决l1范最小问题，对于初学压缩感知的同学有一定的帮助 -L1 norm minimization problem based on least squares ideology, compressed sensing for the beginner students some help
SRC 实现了使用基于稀疏表示的人脸识别算法
- 该源码实现了使用基于稀疏表示的人脸识别算法。使用GPSR作为l1模最小化方法。-This pack of code implement a imges-based face recognition using sparse representation classification. In the algorithm, i employ GPSR as tool to complete the optimization procedure of l1-minimization.
L1
- 目前比较流行的稀疏分解重构程序，可以用在人脸识别、字典构造等方面。-Currently popular sparse decomposition and reconstruction process, can be used in face recognition, dictionary structure and so on.
l1magic
- This package contains code for solving seven optimization problems. -The main directory contains MATLAB m-files which contain simple examples for each of the recovery problems. They illustrate how the code should be used (it is fairly straightfor
irntv
- TV正则化去卷积the Iteratively Reweighted Norm algorithm for solving the generalized TV functional, which includes the L2-TV and and L1-TV problems-An Iteratively Reweighted Norm Algorithm for Minimization of Total Variation Functionals
YALL1-v1.3
- 求解L1范数最小化问题的凸优化工具包，共含有6个模型的求解方法-Solving the L1-norm minimization problem of convex optimization toolkit contains a total of six methods of solving the model
l1_ls_matlab
- 稀疏表达中最小化l1范数问题的求解过程，matlab编写-Sparse expression l1 minimization process of solving the problem of norm, matlab write
l1magic-1.1
- 对l1最小化的处理，其中包括全面的l1范数的解得算法，运用tv全变分最小的解决方法，适合于单像素以及图像处理的研究者参考。(L1 minimization, including the full L1 norm solution algorithm, the use of TV total variation, the smallest solution, suitable for single pixel and image processing researchers reference.)
python_feature_signalgorithm
- 用Python通过L1-penalized minimization problem实现人脸识别算法(Solve an L1-penalized minimization problem with the feature sign search algorithm of Lee et al (2006).)