【摘 要】
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Dear editor,rnWith the ability to reconstruct signals represented using sparse bases in a certain transform domain from an incom-plete set of samples,sparse signal recovery (SSR) has been used in various applications.The reported SSR algorithms include ba
【机 构】
：
College of Electronic Science and Technology,National University of Defense Technology,Changsha 4100
论文部分内容阅读
Dear editor,rnWith the ability to reconstruct signals represented using sparse bases in a certain transform domain from an incom-plete set of samples,sparse signal recovery (SSR) has been used in various applications.The reported SSR algorithms include basis pursuit (BP)[1],orthogonal matching pursuit(OMP)[2],and sparse Bayesian learning (SBL)[3,4].These algorithms are effective for reconstructing one-dimensional(1D) signals from incomplete data.
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