搜索资源列表
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.
l1magic-1.1
- 最小化L1范数求解,通过L1-LS工具包。-L1 norm minimization solution, through the L1-LS kit.
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.
l1-slove
- 压缩感知中求解最优L1范数问题的BP算法内含指导文章-Compressed sensing in L1 norm to solve the problem of optimal BP algorithm article contains guidance
l1benchmark
- l1benchmark 这个算法包提供了十种求解带稀疏约束的矩阵方程 AX=b 的 MATLAB 实现代码,并提供了一个比较各种算法求解结果的演示。-An L1-norm minimization benchmark package, which contains an implementation of ten L1-norm minimization algorithms in MATLAB. The package also provides a test scr ipt for comp
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
l1magic
- L1 minimization and compressive sensing
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
rw_l1
- 用reweighted L1优化进行压缩感知的信号重建算法-Optimized by reweighted L1 signal is compressed sensing reconstruction algorithm
nnLogisticR
- Logistic Loss with the L1-norm Regularization subject to non-negative constraint
SolveHomotopy
- SolveHomotopy.m- l1 minimization Algorithm-SolveHomotopy.m-l1 minimization Algorithm
YALL1_v1.0
- Yall是一个能求解6种不同最小化L1问题的matlab软件包。里面有详细的使用说明和算法求解的基本思路。-It is a Matlab solver that at present can be applied to the six L1-minimization models
l1magic-1.1
- L1 magic L1eq_pd. This code solve linear problem with l1 minimization method.
WrightSIAM12
- Dictionary Learning by L1-Minimization.
Spectral Projected Gradient for L1 minimization
- SPGL1 is a Matlab solver for large-scale one-norm regularized least squares.It is designed to solve any of the following three problems: 1. Basis pursuit denoise (BPDN): minimize ||x||_1 subject to ||Ax - b||_2 <= sigma, 2. Basis pursuit (BP): min
l1eq_pd
- L1 minimization Program Compressive Sensing
l1-norm-recovery
- the recovery of the 2D SAR image with l1-norm minimization
l1-algorithm
- 该软件包包含了合并执行在MATLAB9升-1的最小化算法。每个函数都使用一组参数是一致的(如停止准则和公差)与我们的基准脚本接口。 正交匹配追踪:SolveOMP.m 原对偶内点法:SolvePDIPA.m 梯度投影:SolveL1LS.m 同伦:SolveHomotopy.m 迭代阈值:SolveSpaRSA.m 近梯度:SolveFISTA.m TFOCS:SolveTFOCS.m SesopPCD:SolveSesopPCD.m 原始增强拉格朗日乘子:S
l1 minimization
- minimization algorithm for cs recovery
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.)