张枫;王建军;

• 1:西南大学数学与统计学院

摘要(Abstract)：

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?_2/?_1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δ_(2k|τ)满足0 <δ_(2k|τ)<0.2时,?_2/?_1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界.基于离散傅里叶变换(DFT)字典,执行了一系列仿真实验充分证实了理论结果.

关键词(KeyWords)： 压缩感知;?_2/?_1极小化方法;Block D-RIP;冗余紧框架;块稀疏信号

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(61673015,61273020);; 西南大学实验技术研究项目(SYJ2019031);; 中央高校基本业务费专项(XDJK2018C076,SWU1809002)

作者(Authors): 张枫;王建军;

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