搜索资源列表
RL1
- 基于加权l1范数的稀疏信号重建，稀疏信号是带噪声的-Sparse signal reconstruction based on the weighted l1 norm sparse signal with noise
tutorial-compression-perception
- tutorial压缩感知代码。压缩感知，又称压缩采样，压缩传感。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号-The tutorial compression-aware code. Compressed sensing, also known as compressed sampling, compressed sensing. It as a new sampling theory
ssdp
- 统计稀疏分解（SSDP）欠定盲分离MATLAB仿真程序。能在接收天线个数小于源信号个数时，仅仅利用观察信号恢复出源信号。-Statistics sparse decomposition (SSDP) underdetermined blind separation of MATLAB simulation program. In the number of receiving antennas is less than the number of source signals, using on
WCMSR
- 宽带信号协方差矩阵稀疏表示DOA估计算法仿真-The broadband signal covariance matrix sparse said DOA estimation algorithm simulation
CS_OMP
- 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 the realization of compressed sensing (orthogonal to match the tracking method Orthogonal Matching Pursuit) number of measurements M = K* log (N/K),
SL0
- 非常有用的平滑l0算法代码程序，实现信号的稀疏重构-Very useful for smoothing the l0 algorithm code procedures to achieve signal sparse reconstruction
TestSL0
- 非常有用的平滑l0算法代码程序样例，实现信号的稀疏重构-Very useful for smoothing the l0 algorithm code procedures to achieve signal sparse reconstruction
CS_HelloWorld
- 压缩感知的介绍性算法 主要是介绍OMP算法在稀疏信号重构上的实现-The compressed sensing introductory algorithm is introduced OMP implementations of the algorithm in the sparse signal reconstruction
l1_soc_mljsq_joint
- 一种求解信号DOA的方法。该方法首先将DOA的估计转化为MMV问题，然后采用联合稀疏约束将其转化为带稀疏约束问题的求解。-A method of solving signal DOA. Firstly, the DOA estimates into MMV problem then will be transformed into the solving of the problems with sparse constraint joint sparse constraints.
uwbdete6
- 该方法将宽带信号的检测转化为稀疏信号的表示问题。利用分数阶傅里叶变化实现宽带LFM信号的稀疏表示，然后利用OMP算法实现LFM信号的检测。-The method to the detection of broadband signals into sparse signal representation problem. Wideband LFM signal changes in the fractional Fourier sparse representation, and then ta
l1_norm_compressed-sensing
- 两个l1准则下的噪声干扰信号压缩感知重构举例，两个例子的稀疏矩阵均为DCT矩阵，而观测矩阵分别采用单位阵和随机矩阵，有详细的步骤和使用方法，适用于初步的学习压缩感知方法。-This programme supply two examples by Compressed sensing with l1 norm. The sparse matrix of two examples are all DCT matrix and the obsever matrix are unit matrix a
omp
- omp算法，该编码通俗易懂，应用简单。用于求压缩感知中，在字典D已知的前提下，一个信号在该字典上的稀疏表示。-omp algorithm, and compressed sensing, sparse representation of a signal in the dictionary in the dictionary D known premise.
omp
- 正交匹配追踪算法，是一种压缩感知中的重构算法，优点是复杂度低，缺点是需要预知信号的稀疏度-Orthogonal matching pursuit algorithm is a compressed sensing reconstruction algorithm, the advantages of low complexity, the disadvantage is the need to predict the sparsity of the signal
CS_Primary_tutorial
- CS压缩传感的初级教学代码，使用OMP重构，已注释，包括1维信号，2维图像的重构，分别使用dct和小波稀疏，列扫描和分块法进行omp重构-CS compressed sensing primary teaching code using OMP remodeling, already commented, including a 1-dimensional signals, 2-dimensional image reconstruction, respectively, using the D
signatureSal
- 图像特征是稀疏信号的很好表达，使用简单的操作可以对图像进行恢复。此代码可用于用于图像特征的基准。-the image signature is a good descr iptor for sparse signals, which support can be approximately recovered using extremely simple operations. The MATLAB scr ipts for benchmarking of image signature
k_svd1
- K-SVD同MOD一样也分为Sparse Coding和Dictionary Update两个步骤，Sparse Coding没有什么特殊的，也是固定过完备字典D，使用各种迭代算法求信号在字典上的稀疏系数。-K-SVD Sparse Coding and Dictionary Update is also divided into two steps, like MOD, Sparse Coding is not anything special, also fixed overcomplete
toolbox_sparsity
- 一个很有用的基于稀疏的信号处理工具箱，包含有多种算法。-a useful toolbox based on sparse signal processing
CS(matlab)
- 压缩感知，又称压缩采样，压缩传感。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号。-Compressed sensing, also known as compressed sampling, compressed sensing. It as a new sampling theory, it is through the development signal sparse chara
files
- 压缩感知的很简单的入门小例子，基矩阵为正弦基，能很好地重构出稀疏信号-A simple example for the introduction of CS theory, the basis matrix is sinosoidal matrix, which can fully reconstruct the sparse signal.
ShearLab-PPFT-1.0
- 图形处理中需要用到的剪切小波变换。可以稀疏表示信号。-Graphics processing needed shear wavelet transform. Sparse representation of the signal.