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: 12 Pages.

Download: PDF

Submission history

[v1] 2017-09-28 22:11:39 (removed)
[v2] 2018-05-30 03:56:03

Unique-IP document downloads: 56 times is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus