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Object-Recognition-via-Sparse-PCA 利用稀疏主分量分析实现目标识别中的特征提取
- 利用稀疏主分量分析实现目标识别中的特征提取，包括论文和仿真代码。-Informative Feature Selection for Object Recognition via Sparse PCA
Demo_MWC
- 稀疏信号的压缩感知算法，将宽带稀疏信号通过压缩感知的方法压缩为窄带信号便于传输。-Sparse signal compressed sensing algorithm broadband sparse signals compressed by compressive sensing method for narrowband signals for transmission.
LIyuanqing
- Sparse Representation and Its Applications Yuanqing Li Center for Brain Computer Interface & Brain Information Processing South China University of Technology, Guangzhou, China -Yuanqing Li Center for Brain Computer Interface & Bra
A-Bayesian-Approach
- In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution
PTandCSword
- 基于峰值变换的信号稀疏表示及重建，相关理论说明。-Sparse representation of signals based on peak transform and reconstruction, and related theoretical explanations.
weighted-sparse-array-research
- 在满足技术指标前提下, 采用稀硫天线阵列可以 降低雷达造价。 以 国口 径 天线阵列为例 , 对满阵和稀硫阵的特性进行 比较, 分析了采用 T a yl o r 分布的独立采样和相关采样的密度加权方法的稀硫阵列方向图变化。 结果表明, 阵列 的变稀总伴随 寿方向田的史坏 , 常要经过多次阵列的计葬排列选择以获得满意的稀硫阵列。-Meet the technical indicators under the premise of dilute sulfur an
Sparse-Matrix
- 在处理数据时经常需要处理稀疏矩阵，本文件包含了部分处理稀疏矩阵对角化、行列重拍等Matlab函数。-In the processing of data often need to deal with sparse matrices, this document contains some sparse matrix diagonalization, ranks remake Matlab functions.
201111-291
- 含噪信号的稀疏表示研究，该方法的计算复杂度较低-Sparse representation of noisy signals, the low complexity of the method of calculation
Improved-OMP-Approach-to-Sparse-Multi-path
- this file is a good pdf paper in compressive sensing aparse processing paper. this can be useful and has benefit to all researchers
s
- Sparse Partial Least Squares Regression for On-Line Variable Selection with Multivariate Data Streams
CS
- 信号稀疏分解及压缩感知理论应用研究，理论基础-Signal sparse decomposition and compression perception theory applied research, theoretical basis
Short-duration-power_CS
- 根据压缩传感(Compressed Sensing，cs)N论，首次提出了短时电能质量扰动信号的压缩采样方法，该方法突破了奈奎斯特采样频率的限制，实现了低于奈奎斯特采样频率的低速率采样。文中对比分析了CS理论与传统采样理论，研究了cS短时电能质量信号压缩采样的实现方法，包括：测量矩阵的构建、稀疏基的选取和电能质量信号快速贝叶斯匹配追踪重构算法(FBMP)-Compressed sensing ( Compressed Sensing , cs ) N theory , first propose
Image-reconstruction_CS
- 合稀疏贝叶斯学习(SBL)和可压缩传感理论(CS)，给出一种在噪声测量条件下重建可压缩图像的方法。该方法将cS理论中图像重建过程看作一个线性回归问题，而待重建的图像是该回归模型巾的未知权值参数；利用sBL方法对权值赋予确定的先验条件概率分布用以限制模型的复杂度，并引入超参数- Hop sparse Bayesian learning ( SBL ) and compressible sensing theory ( CS ) , give a compressible image recon
Autofocus-ISAR-Sparse-represetation
- 基于稀疏表示的逆合成孔径雷达自聚焦成像，讲述了自聚焦方法-Based on sparse representation inverse synthetic aperture radar imaging self-focusing
ISAR-sparse-aperture
- 利用稀疏孔径进行逆合成孔径雷达的高分辨成像-Sparse aperture inverse synthetic aperture radar for high-resolution imaging
CompressiveSampling
- 在无线传感器网络中，空间稀疏，高效的压缩采样。-In wireless sensor networks, spatial sparse, efficient compression sampled.
SparseOLS
- implementation ols sparse algorithm
twoDomp
- 基于L阵的二维信号稀疏分解的DOA估计 应用稀疏分解方法进行二维DOA估计-Estimation sparse decomposition method based on two-dimensional signal-dimensional DOA estimation of sparse matrix decomposition L DOA
signal-classification-by-sparse-representation.ra
- this tutorial is about signal classification using sparse representation.
sparse-compressed-sensing
- sparse adaptive processing