期刊
2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
卷 -, 期 -, 页码 2499-2503出版社
IEEE
关键词
compressed sensing; matching pursuit; sparse signal reconstruction; restricted isometry property
Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Various greedy recovery algorithms have been proposed to achieve a lower computational complexity compared to the optimal minimization, while maintaining a good reconstruction accuracy. We propose a new greedy recovery algorithm for compressed sensing, called the Adaptive Reduced-set Matching Pursuit (ARMP). Our algorithm achieves higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to minimization in terms of the normalized time-error product, a metric that we introduced to measure the trade-off between the reconstruction time and error.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据