说明：Sparse signal processing algorithms

说明：Underdetermined DOA estimation for wideband signals using robust sparse covariance fitting

说明：Matlab编写的移不变稀疏分解程序 ,求得对应于不同源信号的基，可实现信号特征提取

说明：低秩矩阵恢复对齐， 论文 Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images

说明：one can see that the pattern corresponding to the finite difference discretization tends to be a banded and highly sparse matrix. The same pattern of matrix resulting from discretization arises when we deal with the three-dimensional problem. Figure (2.3) shows the pattern of the matrix arising when solving the three dimensional Poisson equation using similar finite difference approximation.

说明：MATLAB implementation of compressive sensing example as described in R. Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118], July 2007. The code acquires 250 averaged random measurements of a 2500 pixel image. We assume that the image has a sparse representation in the DCT domain (not very sparse in practice). Hence the image can be recovered from its compressed form using basis pursuit.

说明：MATLAB implementation of compressive sensing example as described in R. Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118], July 2007. The code acquires 250 averaged random measurements of a 2500 pixel image. We assume that the image has a sparse representation in the DCT domain (not very sparse in practice). Hence the image can be recovered from its compressed form using basis pursuit.

说明：目标追踪。低秩稀疏编码学习，稀疏编码，sift

说明：Matrizes esparsas na linguagem C.

说明：这本书在稀疏的多尺度图像和信号处理提出了艺术状态，包括线性多尺度变换，如小波，脊波和曲波变换、非线性、多尺度变换基于中值和数学形态学算子。最近的稀疏性和形态多样性的概念描述和利用各种问题，如去噪，反问题正规化，稀疏信号分解，盲源分离，压缩感知。 这本书的理论和实践研究相结合的领域，如天文学、生物学、物理学、数字媒体应用和取证。最后一章探讨了信号处理中的一个范式转换，表明以前的信息取样和提取的限制可以用非常重要的方法加以克服。 MATLAB和IDL代码伴随这些方法和应用程序重现。 实验并说明了在相关网站上可下载的研究的推理和方法。

说明：This document contains documentation on how to use the Long Term Evolution (LTE) System Level simulator [1] as well as some insight on its structure and the assumptions that were made while developing it. This document relates more on how to actually use the simulator. The concept and the structure of the simulator is described in more detail in [2].

说明：实现稀疏典型相关分析算法,,matlab 语言实现，仅作为一个示例

说明：现在LLE算法已经广泛应用于图像数据的分类与聚类、文字识别、多维数据的可视化、以及生物信息学等领域中。我目前所做的工作是基于Sparse Representation的Super Resolution

说明：DOA 估计里面的off-grid对应的原版MATLAB程序，SCI期刊论文程序《Off-Grid Direction of Arrival Estimation Using Sparse Bayesian Inference》，用于高精度测量DOA。

说明：Nonlocally Centralized Sparse Representation for Image Restoration

说明：efficient sparse coding, fast feature sign search algorithm, convex optimization

说明：sparse face recognition

说明：an open-source optimization toolbox for sparse estimation with licence GPLv3

说明：a new android game for you because is very important game

说明：新的回归向量机，用于回归拟合，相关论文可以参考sparse bayesian learning and relevance vector machine

说明：有关于论文稀疏监督下的GAMP算法应用代码

说明：通过字典学习更新的方法，对图像信号进行稀疏化分解

说明：这是文章《Sparse Representation For Computer Vision and Pattern Recognition》的对应的稀疏表示代码，非原创，转载而来，供大家交流学习。

说明：中心稀疏表达去除高斯噪声，iccv会议论文源码，内含文献，原文题目Centralized Sparse Representation for Image Restoration

说明：Linear Spatial Pyramid Matching using Sparse Coding for Image Classification

说明：利用匹配追踪对信号进行稀疏分解，得到其稀疏表示形式

说明：Segmentation Based Sparse Reconstruction

说明：Dimensionality Reduction for Sparse Representation

说明：本程序实现稀疏主成分分析，相关方法在 H. Zou, T. Hastie, and R. Tibshirani的Sparse principal component analysis中有详细介绍

说明：Sparse Concept Coding for Visual Analysis