搜索资源列表
l1
- 压缩感知的一个应用实例，对压缩后的信号用BP算法重构-An application of compressed sensing, on the compressed signal with the BP algorithm has
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
SparseLab21-Core
- 一种基于压缩感知技术的图像重建程序，可以提高图像重建质量和速度-Compressed sensing technology based on the image reconstruction process, can improve the quality and speed of image reconstruction
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
GPSR
- 压缩感知信号重建 梯度投影法信号重建代码-Compressed sensing signal reconstruction signal reconstruction code gradient projection method
regular_omp
- 压缩感知的一个恢复算法，规则化正交匹配追踪-A recovery algorithm for compressed sensing, rules-based orthogonal matching pursuit
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 。
BCS_
- 贝叶斯压缩感知的仿真程序，此程序使用LAPLACE先验，-This is a simple example to test the fast Laplace algorithm from the following paper: S. D. Babacan, R. Molina, A. K. Katsaggelos. bayesian Compressive Sensing using Laplace Priors
CS
- Matlab编写的压缩感知的库函数，包括稀疏分解和重构。-Written in compressed sensing Matlab library functions, including the sparse decomposition and reconstruction.
MinTV_Test
- 采用MinTV算法对图像进行处理，用MinTV恢复算法+牛顿迭代法实现压缩感知对图像的处理。-MinTV algorithm using image processing, with MinTV recovery algorithm+ Newton iteration method to achieve compression perception of the image processing.
dct_cs
- DCT压缩感知方案，采用DCT基稀疏分解原始信号，并且重构出原始信号-DCT compressed sensing scheme, using sparse decomposition of the original DCT-based signal and reconstruct the original signal
CoSaMP_singlel
- 压缩感知中的迭代恢复算法，是匹配追踪的一种变形。Cosamp稀疏恢复算法。-Iterative restoration in compressed sensing algorithm is a variant of matching pursuit. Cosamp sparse recovery algorithm.
sparse
- 基于压缩感知的图像融合程序 matlab编写-Compressed sensing image fusion based program written matlab
block_mp
- 压缩感知里面的稀疏重建问题，在原来MP的算法的基础上，提出了分块的思想，即将原子库分块后，测试算法的性能。-Compressive sensing is refered as the block sparse algorithm is described,that is based on the original MP algorithm,and the atom libruary is divided into blocks ,and the performance is testified.
hadamard
- 压缩感知算法中观测矩阵为哈达玛矩阵重构算法为OMP时的测量相对误差与观测矩阵维数的关系-Compressed sensing algorithm for the Hadamard matrix of observation matrix reconstruction algorithms for the OMP and the relative error when measuring the dimension of the relationship between the observed
CS_OMP
- 压缩感知信号重建的正交匹配追赶算法（omp），与bp算法相比较有叫高的精度，但是付出了计算量的代价-Compressed sensing signal reconstruction algorithm Orthogonal matching catch (omp), compared with the bp algorithm are called high precision, but at a cost of computation
csreview
- 压缩感知综述，包含中文和英文的论文，描述最新的理论及算法-Summary of compressed sensing, including Chinese and English papers, describes the latest theory and algorithm
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，
BP_Simplex
- 使用BP算法实现压缩感知信号重构,需要已知观测空间基矩阵和观测向量-BP_Simplex,BP with a Simplex mplementation