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基于冗余紧框架的ℓ2/ℓ1极小化块稀疏压缩感知

Authors: 张枫;王建军

压缩感知是(近似)稀疏信号处理的研究热点之一,它突破了Nyquist/Shannon采样率,实现了信号的高效采集和鲁棒重构.本文采用ℓ2/ℓ1极小化方法和Block D-RIP理论研究了在冗余紧框架下的块稀疏信号,所获结果表明,当Block D-RIP常数δ2k| 满足0 < δ2k| < 0.2时,ℓ2/ℓ1极小化方法能够鲁棒重构原始信号,同时改进了已有的重构条件和误差上限.基于离散傅里叶变换(DFT)字典,我们执行了一系列仿真实验充分地证实了理论结果.

Comments: 10 Pages.

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[v1] 2017-09-28 22:11:39

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