搜索资源列表
Wavelet_OMP
- 本程序实现图像LENA的压缩传感,包括图像的稀疏表示，图像重构等等子函数，运行效果良好-The program image LENA compressive sensing, including the sparsity of the image, image reconstruction, and so subfunction running well
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_explain_radar
- 压缩感知在雷达中的应用 很好的一个介绍 雷达成像中惯用的方法是匹配滤波，它之所以 能够处理低信噪比的问题，是因为它利用了回波数据的冗余信息。也就是目前雷达成像算法之所以成功的关键是具有足够 多的冗余信息。现在，在雷达成像中使用压缩感知恰好是反其道而行-Compressed Sensing(CS)theory is a great breakthrough of traditional Nyquist sampling theory，it accomplishes cornpressive
Blind-Deconvolution-
- Blind Deconvolution Using a Normalized Sparsity Measure 的代码-matlab code for Blind Deconvolution Using a Normalized Sparsity Measure
generate_graphs
- MIT稀疏傅里叶变换 小组的SFFT 源码： 运行的SFFT和FFTW参数和重复的范围内，两者的运行时间 诗句信号的大小（n）或稀疏（ K ） 。重新创建图表的文件： 稀疏傅里叶变换， SODA 12简单和实用的算法。 -Runs sFFT and FFTW for a range of parameters and plots the runtime of both verse the signal size (n) or the sparsity (k). Recreat
subspace_J21
- Input: X, training data, dim*num Y, training data labels, num*class para.alpha, para.beta, regularization parameters para.rd, reduced dimensionality Web Image Annotation via Subspace-Sparsity Collaborated Feature Selection. Zh
inpaint
- 基于压缩感知的图像修复,，基于图像在复数小波变换上的稀疏性，利用迭代硬阈值方法 求解重构模型，进而获得重构图像.-Based on compressed sensing image restoration, image-based complex wavelet transform on the sparsity of the iterative method for solving hard threshold reconstruction model, and then get the
3-3-1
- 基于图像的稀疏性用OMP算法对图像去噪，思路清晰，容易理解-Based on the sparsity of the image with OMP algorithm for image denoising, clear, easy to understand
modelcs_v1.1
- modelcs_v1.1 - 1D trees, 2D trees, Block sparsity, Clustered sparsity
LSL_SC
- based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the mini
spgl1-1.8
- based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to
4.8k_CELP
- 语音CELP压缩解压源代码（C语音)- Pronunciation CELP compression decompression source code (C pronunciation) - * 4800 bps CELP Characteristics * * Spectrum Pitch Code Book * ------------- ---------------
SAMP
- 稀疏自适应匹配追踪算法，无需稀疏度，就可以重构原始信号。-Sparse adaptive matching pursuit algorithm, without sparsity, we can reconstruct the original signal.
CoSaMP
- CoSaMP算法，在重构信号时，选取两倍稀疏度的原子来恢复原始信号，再删去一倍稀疏度的原子。-CoSaMP algorithm, in the reconstructed signal, select twice the atomic sparsity to recover the original signal, and then deleting the double sparsity of atoms.
CSR_Denoising
- Weisheng Dong and Xin Li. "Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering"基于聚类的图像稀疏去噪这篇论文的去噪代码。-Weisheng Dong and Xin Li. " Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering" C
BCS-SPL-1.5-new
- Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as comp
PoissonRecon
- Poisson surface reconstruction creates watertight surfaces from oriented point sets. In this work we extend the technique to explicitly incorporate the points as interpolation constraints. The extension can be interpreted as a generalization of
LASSOaLARSa-SPCA
- Abstract There a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (
SAMP1
- 能对压缩感知中的稀疏度未知的信号精确的重建，重建误差小，经本人调试，完全正确-Capable of compressed sensing signals unknown sparsity accurate reconstruction, reconstruction error is small, after I debug, completely correct
4-chapter
- 信号稀疏度检测的matlab仿真程序。该方法能够检测出宽带信号的稀疏度，保证Compressive Sensing在宽带频谱检测中的准确运用。-Signal sparsity detection matlab simulation program. The method can detect the wideband signal sparsity ensure Compressive Sensing wideband spectrum sensing in the exact use.