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压缩传感引论(沙威博士)：压缩感知如门级文章，对正交匹配追踪算法进行了详细的阐述。-Compressed sensing cited theory (Savit Ph.D.): compressed sensing, such as gate-level article on the orthogonal matching pursuit algorithm in detail.
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基于Gabor感知多成份字典，进而提出一种高效的基于匹配追踪的图像稀疏分解算法，很有参考价值！-An effective algorithm based on the matching pursuit method is posed to obtain sparse decomposition of image with Gabor dictionary!
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matching pursuit 算法是信号分解的一种具体实现方法。但其本质上则是一种估计
信号模型参数的方法，因而可直接用于信号检测及参量估计。本文以谐波信号特征参量的估计为例，介绍了其具体实现方法。-matching pursuit algorithm is a specific method of signal decomposition. But by its very nature is an estimated signal model parameters, and thus
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this document is used for algorithm matching pursuit and omp enjoy
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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
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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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The problem of optimal approximation of members
of a vector space by a linear combination of members
of a large overcomplete library of vectors is of importance
in many areas including image and video coding,
image analysis, control theory, a
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In this paper, we propose a novel compressive
sensing (CS) based approach for sparse target counting and
positioning in wireless sensor networks. While this is not the
first work on applying CS to count and localize targets, it
is the first t
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基于子空间方法的联合稀疏恢复，通过MUSIC算法进行结合测试，给出了测试结果-We propose subspace-augmented
MUSIC (SA-MUSIC), which improves on MUSIC such that the
support is reliably recovered under such unfavorable conditions.
Combined with a subspace-based greedy algorithm, known
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使用matlab实现智能预测控制算法，匹配追踪和正交匹配追踪，Matlab实现界面友好。- Use matlab intelligent predictive control algorithm, matching pursuit and orthogonal matching pursuit, Matlab to achieve user-friendly.
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