搜索资源列表
dct_cs
- 采用BP算法来实现压缩感知的信号重构示例。BP算法由线性规划来实现，稀疏基为DCT基，信号为语音信号-an example of using BP algorithm for signal reconstruction in compressed sensing. BP algorithm is implemented by linear programming, sparse basis is the DCT basis, the signal used is speech
BCS_MP
- 压缩感知的仿真程序，此程序使用OMP算法，实现对一维输入信号的重构-This package includes 2 folders. Folder mp contains mp algorithmn and Folder omp contains omp algorithmn 。
cs-code
- 一个正弦波利用DCT，FFT变换后稀疏化，然后应用压缩感知实现压缩，并有仿真图例说明重构效果。重构算法采用线性规划和OMP算法等，是一个初学CS入门的好例子。-A sine wave using DCT, FFT transform sparse, and then apply compressed sensing to achieve compression, and a legend reconstruction simulation results. Reconstruction algo
compress edsensing OMP
- 压缩感知 正交匹配追踪一些人关心压缩感知与雷达成像，他们把稀疏表示放在最重要的地方，以为在雷达成像中成功实现压缩感知关键是稀疏表示； 事实上并不是如此。我们知道：压缩感知需要建立AX=B,且该方法具有较低的抑制信噪比能力；另外雷达成像的基础是雷达 信号与目标的相互作用，也就是电磁波与介质的相互作用，该相互作用是一个非常复杂的非线性问题，因此研究这个问题与 压缩感知的关系才是解决雷达成像问题的关键点所在。从另外一个角度来看，雷达成像中惯用的方法是匹配滤波，
l1magic-1.1
- 实现对图像的分块并进行压缩感知算法的恢复-Achieve the right image sub-block and recovery of compressed sensing algorithm
Compressive-Sensing
- 压缩感知简介,包括压缩感知具体实现过程，最基本的原理说明-compressive sampling
MP2
- 压缩感知， 匹配追踪， 是MP算法的另一种实现，该代码严格按照算法，运行可靠-compressive sensing match pursuit another MP algorithm .both MP and MP2 can work well
matlab
- OMP算法的一维信号实现matlab 源码 基于压缩感知的-OMP algorithmn
CS_OMP
- 压缩感知方法演示，1-D信号压缩传感的实现(正交匹配追踪法Orthogonal Matching Pursuit) 测量数M>=K*log(N/K),K是稀疏度,N信号长度,可以近乎完全重构-1-D signal is compressed sensing to achieve (orthogonal matching pursuit method Orthogonal Matching Pursuit) number of measurements M> = K* log
romp
- 实现压缩感知的快速重构算法！算法简单易于实现-Reconstruction from partial Fourier data
smp
- 用smp算法实现基于压缩感知的磁共振图像重构-Smp algorithm for image reconstruction based on compressed sensing
OMP
- 这里主要是压缩感知的贪婪算法，通过OMP来实现DOA的估计，主要应用在阵列信号处理领域。-Here compressed sensing greedy algorithm OMP, the main application in the field of array signal processing to achieve the DOA estimates.
YALL1_v1.4
- 上述程序是美国RICE大学的一个学生编写的用于压缩感知的恢复算法，可以实现很多模型的稀疏恢复，包括BP，l1,l2,l1-l2混合型等比较多的类型-The above procedure is a student of the University of the United States RICE prepared for compressed sensing recovery algorithm can achieve a lot of model sparse recovery, incl
BSSPCS
- 相关的 BSS 盲源分离问题和 CS压缩感知的结合4篇论文打包，以及一个声音信号混合分离的简单实现-the realization of BSS(blind source separation) and CS(compressed sensing), and a sample of volume signal
压缩感知MRI
- CS_MRI:压缩感知（CS）在MRI领域的应用.程序实现展示了CS在MRI的重要作用和明显效果。对于那些CS初学者有着极大的帮助。
KFCS_new
- 将卡尔曼滤波的方法与压缩感知联系在一起，实现对动态压缩感知信号的恢复。(combined the kalman filter and compressed sensing, to realize the recovery of dynamic signal.)
doa-limagic
- 基于压缩感知的一种信号重建方法，l1magic工具包，利用此种方法实现压缩感知理论。(A Signal Reconstruction Method Based on Compressed Sensing,l1magic)
omp
- 压缩感知重构算法之正交匹配追踪(OMP)的算法实现(Implementation of Orthogonal Matching Pursuit (OMP) algorithm for compressed sensing reconstruction)
sparseMRI_v0.2.tar
- 代码是关于压缩感知磁共振成像的具体实现，运行环境为MATLAB，十分经典的代码(The code is about the realization of compressed perceptual MRI. The running environment is matlab, which is a very classic code)
CS_OMP
- 是关于压缩感知磁共振成像的正交匹配追踪算法的具体实现，用于稀疏磁共振成像，可以进行仿真实验(The code is about the realization of compressed perceptual MRI. The running environment is matlab, which is a very classic code)