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image_smoth
- 稀疏分解的匹配追踪程序，用新的较少的原子来重建信号或图像，使信号或图像的表示更加简洁。-MP tracking procedures, with new atomic less to rebuild signal or image the signal or image said more concise.
low_high
- 稀疏分解信号重建程序，利用匹配追踪原理不断对信号匹配，最后达到重建信号目的。-sparse decomposition signal reconstruction procedures, the use of matching principle constantly tracking the signal matching, Finally signal to the redevelopment purposes.
mp_initial
- 稀疏分解严格按照匹配追踪的原理，生成新的原子，对信号匹配，直至剩下信号残差。-sparse decomposition in strict accordance with the principle of matching the track, a new generation of atomic bombs, the signal matching, until the remaining residual signal.
MPTFcomposition
- 实现信号基于MP的稀疏分解，并对信号进行时频分布
SignalandImageDecompositionandItsPreliminaryApplic
- 信号与图像的稀疏分解及其初步应用，包含详细算法-Sparse signal and image decomposition and its preliminary application, contains a detailed algorithm
A_wavelet_tour_of_signal_processing
- 由著名小波大牛mallat最新写的关于小波变换信号处理的书，里面包括小波变换的最新进展。如稀疏矩阵，压缩传感等概念-Daniel mallat by well-known wavelet-date written on the wavelet transform signal processing books, which include the latest developments of wavelet transform. Such as sparse matrix, the concep
CS
- 用matlab利用压缩感知CS实现对一位信号的处理~小波稀疏分解，正交追踪算法重构~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-CS with matlab using compressed sensing to achieve a sparse signal processing- wavelet decomposition, the orthogona
erzhituxiangCS
- 读取二值图像，转化为稀疏信号，变换到压缩域，然后用压缩感知进行重构。-Read binary image, into sparse signal, transform to the compressed domain, and then use compressed perception reconstruction
lectures-about-CS-and-SpaRec
- 一些关于压缩传感的基础性、系统性的介绍和一些稀疏信号重构算法的介绍如FOCUSS和Greedy Algorithm,适合入门人学习的资料-Some basis and system lectures about compressive sensing also including some sparse signal reconstruction algorithm for you such as FOCUSS and Greedy MP.all the materials are fit fo
SparsePOP122
- 信号的稀疏化 信号的稀疏化 -sparse signal sparse signal sparse signal sparse signal
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
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),
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
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
3
- 信号稀疏度K与重构成功概率关系曲线绘制例程代码-K signal sparsity and Reconstruction success probability plots draw sample code
l1_ls
- l1范数约束的使用最小二乘法计算观测信号的稀疏编码，(L1 norm constraint using the least squares method to calculate the observed signal sparse coding,)
sfft-0.1.0
- 采用MATLAB编程实现二分查找法的稀疏傅立叶变换算法。研究算法参数变化对信号频谱的影响，并对特定的宽带跳频信号进行稀疏傅立叶变换处理，得出相应的频谱，并与快速离散傅立叶变换的结果进行比较。(Recurrence of sparse Fourier transform)
K-SVD_and_W_KSVD_Sparse_Representation
- 通过字典学习更新的方法，对图像信号进行稀疏化分解(Through the method of learning and updating the dictionary, the image signals are sparse decomposed)
新建文件夹 (2)
- 字典学习。比如一个向量，是k维的，我现在有一个k*n的字典，其中n>>k，所谓的字典学习，就是在这包含n个向量的字典当中寻找一个线性表示可以表示出当前这个k维的向量。之所以称为“稀疏表示”，因为一般n大于k，比如n=512,k=64。这时候你的字典一定是一个Redundant（冗余的，过剩的）的。因此你的表示里面一定有很多系数为0，因而被称作稀疏表示。 信号稀疏表示的目的就是在给定的超完备字典中用尽可能少的原子来表示信号，可以获得信号更为简洁的表示方式，从而使我们更容易地获取信号中
An improved sparse component analysis Assembly
- 改进的盲源信号分析代码程序集，内有4个例子，对应论文为"Identification of modal parameters using an improved sparse blind source separation".