量化压缩感知的方法
信息论
2016-01-01 v1 math.IT
数值分析
摘要
在本文中，我们比较并编目了各种从量化压缩测量中重建稀疏信号的贪婪量化压缩感知算法的性能。我们还引入了两种新的贪婪重建方法：量化压缩采样匹配追踪(Quantized Compressed Sampling Matching Pursuit, QCoSaMP)和用于量化迭代硬阈值(Quantized Iterative Hard Thresholding)的自适应离群值追踪(Adaptive Outlier Pursuit for Quantized Iterative Hard Thresholding, AOP-QIHT)。我们比较了给定位深、稀疏度和噪声水平下贪婪量化压缩感知算法的性能。
引用
@article{arxiv.1512.09184,
title = {Methods for Quantized Compressed Sensing},
author = {Hao-Jun Michael Shi and Mindy Case and Xiaoyi Gu and Shenyinying Tu and Deanna Needell},
journal= {arXiv preprint arXiv:1512.09184},
year = {2016}
}