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介绍了压缩感知，Compressive Sensing的基本原理
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压缩传感是一个从2006年左右开始兴起的研究领域，它关注于如何采样信号，也就是信号的采样方式或者压缩方式。通过设计一种特殊的采样方案，可以使得采样频率降低为信号的“信息率”，而不是传统的奈奎斯特采样率，于是，实际的采样率可以大大低于奈奎斯特频率，却只损失很少的信息量，依然保持了充足的信息量足以恢复出采样前的原始信号。这个研究思想挑战了奈奎斯特频率的理论极限，会对整个信号处理领域产生极其深远的影响，同时，信号处理的许多应用领域也会随之发生根本性的发展和变化。
-Compressive sens
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求解l1优化问题，在压缩传感中有应用，概算发可以求解三个模型：BP，BPDN和约束版本-Solves L1 problems arsing from Compressive sensing, compressive sampling and sparse optimization
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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.
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新近更新的几篇中文应用类文献，有关Compressive sensing在脑电信号以及UWB中的应用，附带2D小波变换PPT.-The literature of the newly updated several Chinese language paper reference, Compressive sensing in the brain signals and UWB applications, with the 2D wavelet transform PPT.
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基于压缩感知（compressive Sensing）理论在雷达成像上的应用的Pdf文章，对理解压缩感知的应用有重要的帮助。-The application of Compressive Sensing（CS）theory on Radar Imaging.they are helpful for the researchers in CS field.
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压缩感知和超分辨率论文，关于如何将低分辨率的图像如何重建成高分辨率图像，很有用-compressed sensing and super resolution
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this file is a good pdf paper in compressive sensing aparse processing paper. this can be useful and has benefit to all researchers
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this file is a good pdf paper in compressive sensing aparse processing paper. this can be useful and has benefit to all researchers
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Compressive sensing(baraniuk)
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Compressive Sensing(Fornasier Rauhut)
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theory and applications of compressive sensing
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稀疏表达及其应用的简单介绍，其中涵盖了稀疏表示、特征提取、压缩感知、图像增强、盲源分离、模式分类、目标跟踪和图像超分辨等。PPT和PDF是对应的，并添加了可视化的结果。-Sparse Representation and Its Application: Compressive Sensing, Visual Feature, Image Enhancement, Blind Source Separation, Pattern Classification, Object Tracking a
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compressive sensing theory
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compressive sensing theory
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compressive sensing theory
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compressive sensing theory
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压缩感知中经典算法的matlab代码，如包含典型的匹配追踪算法，子空间追踪算法等等。-Compressed sensing classical algorithm matlab code, such as those containing the typical matching pursuit algorithm, subspace tracking algorithms and so on.
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compressive sensing using OMP
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本文提出基于压缩感知的被动式目标轨迹测绘算法，仅用少量观测数据一次性精确测绘出目标轨迹，减少了计算和通信开销，降低了能耗。-In this paper, a passive object trajectory mapping algorithm based on compressive perception is proposed. Only a small amount of observation data can be used to accurately plot the target
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