搜索资源列表
MN_music
- 最小范数MUSIC算法，低SNR和小样本以及高相关情况下MN-Music效果相对较好,提高分辨力，适用于等距线阵。-MN-Music for DOA
L1-norm-unliner
- 最优化一范数的线性拟合，巧妙转化为线性回归问题，避免了一范数不可微的缺点-Optimization of a linear fit the norm, cleverly converted into a linear regression problem, avoiding a non-differentiable norm shortcomings
MPTK-Source-0.6.1.tar
- 求解L1范数的基本方法或者稀疏矩阵的基本方法-MP algorithm based program
BP-procedure
- 基追踪算法，BP，求解压缩感知一范数模型-Basis puisuit algorithm used for Comprssed sensing model
IRLS
- 迭代加权二范数算法,又称FOUCSS，一种求解基于p范数的压缩感知模型算法-FOCUSS algorithm
Denoising-image-combined
- 联合矩阵F范数的低秩图像去噪。好文章供你参考。-Denoising image combined with low rank matrix F norm. Good article for your reference.
l1_eq
- 最小化l1范数求解函数，用于稀疏表示算法，可用该函数求解表示系数。
l1eq_pd
- 稀疏表示，最小化l1范数求解表示系数的函数-sparse representation,minimum
TNNR_DODE_LQ_SELF
- 截断的核范数，可用于矩阵恢复。需要知道丢失点的像素位置。该算法是 2013 PAMI上一篇文章里的算法。感兴趣的-Nuclear norm truncated matrix can be used for recovery. Need to know the pixel positions lost points. The algorithm is an article on the 2013 PAMI algorithms. Look interested
OSIC
- OSIC（排序的连续干扰消除）信号检测仿真程序，实现不同的OSIC信号检测方法：基于SINR排序、基于列范数排序、基于检测后的SNR排序-OSIC (ordered successive interference cancellation) signal detection simulation program OSIC achieve different signal detection method: SINR based sorting, sorting based on the norm
Poisson_J
- J法解Poisson方程，通过迭代输出结果并画图，结果包含迭代步数以及无穷范数-Solution of Poisson equation by J method, iterative output results and drawing, the result contains iteration step number and infinite norm
Poisson_CG
- CG法解Poisson方程，通过迭代输出结果并画图，结果包含迭代步数以及无穷范数-Solution of Poisson equation by CG method, iterative output results and drawing, the result contains iteration step number and infinite norm
Poisson_SOR
- SOR法解Poisson方程，通过迭代输出结果并画图，结果包含迭代步数以及无穷范数-Solution of Poisson equation by SOR method, iterative output results and drawing, the result contains iteration step number and infinite norm
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
scnrm2
- Fortorn种求解2范数的子程序已经验证过可以使用-Beg 2 norm
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
super-resolution-Regularization-
- 本程序包括了三个程序，L1范数正则化，L2范数正则化，Tikhonov正则化超分辨率重建。经反复测试，没有BUG。-The program includes three procedures, L1 norm regularization, L2 norm regularization, Tikhonov regularization super-resolution reconstruction. After repeated testing, no BUG.
ESRC_classifier_v1.1
- 极限学习机\极速学习机\ELM 稀疏表示人脸识别\稀疏表示\L0范数求解 基于ELM与稀疏表示的混合人脸识别算法 AR人脸识别准确率95 . 文章:Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artific
erfanshufangfa_guji_1
- 动目标参数估计，二范数方法，对目标进行速度方向等的估计-Moving target parameter estimation, two norm method, estimate of the target velocity direction, etc.
sparse_fusion
- 运用最小二乘和一范数约束求解低分辨率多光谱图像和高分辨率全色图像融合成高分辨率多光谱图像，程序附带主流的图像融合评价标准，需要融合的图像，对比图像；以及附带程序所需的稀疏包-Using least squares and a norm constraint solving low-resolution multi-spectral image and panchromatic image fusion into a high-resolution multi-spectral images, t