搜索资源列表
l1_ls
- 最小化l1范数的Matlab代码。求解模型为： min lambda*|x|_1+||A*x-y||_2。其中，|x|_1表示x的1-范数，||*||_2表示2-范数。该模型在稀疏成分分析、压缩传感器等领域有广泛的用途。- l1-Regularized Least Squares Problem Solver l1_ls solves problems of the following form:
l1magic-1.1
- 基于matlab的稀疏表示中L1范数计算源码-the codes for L1 in sparsty representation with matlab
project_onto_simplex
- l1范数的投影源码,用于高维的机器学习问题-L1 projection source codes
l1_ls_matlab
- 基于BP算法的 求解最优L1范数的程序和文章-BP algorithm based on L1 norm for solving optimal procedures and articles
l1magic
- 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
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
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-Homotopy-ALM
- 基于稀疏表示的人脸识别，里面有9种求1范数的方法-Face recognition based on sparse representation, there are nine kinds of seeking a method of norm
l1_OMP_matlab
- 压缩感知 L1范数最小化算法正交匹配追踪法重构信号-compressive sensing L1-norm OMP signal reconstruction
BIHT-l1
- 为了解决二进制CS而编写的算法，使用了用l1范数最小化-an algorithm for binary CS，use l1 norm
L1
- 基于L1范数的多帧图像超分辨率图像重建算法，在原有算法基础上改进，提高重建精度和效率。-Based on the L1 norm of the multi-fr a me image super-resolution image reconstruction algorithm, the improvement on the basis of the original algorithm to improve the reconstru
L1-Ls
- 很经典的L1范数算法，可以用于对优化算法的改进，有效加快运算速度和优化精度！-Classic L1 norm algorithm, the optimization algorithm can be used effectively to accelerate the speed of operation, and optimization precision!
l1-ls-A-Matlab-Solver
- 求解L1范数最优化的一个程序包，里面包括源码、说明文档及相应论文-l1 ls A Matlab Solver for Large-Scale ℓ 1-Regularized Least Squares Problems
l1
- 用稀疏表示人脸识别，其中在求解l1范数的部分的matlab源码。-Sparse representation for face recognition, solving l1 norm matlab source.
Approximation-method--BPs-l1-norm
- 基于BP的l1范数逼近法-Approximation method based on BP s l1 norm
l1-Norm-Minimization
- 该文章介绍了L1范数最小化问题稀疏求解的快速算法-This article describes a quick way L1 norm minimization problem solving sparse
L1 SVD
- 利用压缩感知实现波达方向估计，运用奇异值分解对接收信号进行降维，再利用L1范数进行估计(The DOA estimation is realized by compressed sensing, and the singular value decomposition is used to reduce the received signal, and then the L1 norm is used to estimate the D
l1_ls
- l1范数约束的使用最小二乘法计算观测信号的稀疏编码，(L1 norm constraint using the least squares method to calculate the observed signal sparse coding,)
l1-uwa-master
- 感觉这份代码中最有价值的应该是水声信道的建模，该源码来自美国 Parastoo Qarabaqi, Northeastern University, 2013其次其提供了基于l1范数下PCA处理算法，来对经由水声信道的信号进行处理给出误码率图，启动比较程序需要先使用信道生成函数对信号进行生成。(The most valuable part of this code is the modeling of underwater acoust
L1范数代码
- 动态压缩感知（DSC）是压缩感知领域中一个重要的研究分支，它是近几年新兴起的一种信号处理与分析方法，与传统的压缩感知理论不同，DSC研究的对象是稀疏时变信号，并且已在视频信号处理和动态核磁共振成像等方面显示出了强大的应用潜力。本节正是在此基础上，提出了一种用于多普勒频率跟踪估计的DSC方法。首先，通过前一跟踪时刻所得到的先验DOA稀疏信息，获得当前跟踪时刻信号向量中各位置非零元素的分布概率，继而建立起动态DOA的稀疏概率模型。然后，采用