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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
- 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
Compressive_Sensing
- lp范数最小化求解的问题，关于压缩感知的最新文档-lp-norm minimization problem solving, perception of the latest documentation on the compression
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
2012_1217_MMSE
- L1最小范数约束压缩感知算法,提供一个程序参考, it is MATLAB code-L1 norm constraint compressive sesing,it is MATLAB code
cs_bp
- 压缩感知中用到的一种稀疏重构算法，基于求解最小1—范数解。-Compression The perception used a sparse reconstruction algorithm based on solving the minimum 1- norm solution.
l1-norm-recovery
- the recovery of the 2D SAR image with l1-norm minimization
LICS
- 该文章为压缩感知重构算法，主要介绍基于LI范数最小化的凸优化算法，简单实用，比较适合除学着实用。-This article is compressed sensing reconstruction algorithm introduces LI norm optimization algorithm based on minimization of a convex, simple and practical, more suitable in addition to learn practic
NSL0-2D
- NSL0:基于光滑l0范数和修正牛顿法的压缩感知重建算法，是本人精心编写调试好的，请放心使用。-NSL0: compressive sensing reconstruction algorithm based on smooth l0 norm and modified Newton method
NSL0_2D_2
- 2维光滑l0范数和修正牛顿法的压缩感知重建算法，涉及两个测量矩阵，两个方向。是我精心编写的，能通过测试。-2D-NSL0: based on the smooth l0 norm and the modified Newton method of 2 dimensional compressive sensing reconstruction algorithm, involving two measurement matrix, two directions.