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Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems. This is b
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聚集结构压缩感知重建代码，和论文Bayesian compressive sensing for cluster structured sparse signals Signal Processing对应-cluster structure compressive sensing reconstruction code；corresponding to the paper Bayesian compressive sensing for cluster structured sparse si
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Linear prediction (LP) is an ubiquitous analysis
method in speech processing. Various studies have focused on
sparse LP algorithms by introducing sparsity constraints into
the LP framework. Sparse LP has been shown to be effective in
several issu
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基于接收矩阵的稀疏重构，L1-SVD，阵列信号处理方面(Based on the sparse reconstruction of the received matrices, L1-SVD, array signal processing is presented)
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稀疏与冗余表示-理论及其在信号与图像处理中的应用一书的源代码(Sparse and redundant representation -From theory to application in signal and image processing -- the source code of the Book)
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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所蕴含的信息，更方便进一步对信号进行加工处理，如压缩、编码等。信号稀疏表示方向的研究热点主要集中在稀疏分解算法、超完备原子字典、和稀疏表示的应用等方面。(Signal sparse representation is to overcomplete dictionary given in as little as possible to represent atomi
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