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Compressed sensing(CS) is a newly developed theoretical framework for information acquisition and processing,which shows that sparse signals can be recovered exactly from far less samples than those required by the classical Shannon-Nyquist theorem.The block-sparse signal recovery algorithm under the compressed sensing framework was mainly studied,and a class of improved exact recovery conditions based on the block restricted isometry property(RIP) were established in the noiseless cases via the mixed l2/lq(0引文[1]DONOHO D.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
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