摘要
压缩感知理论是利用信号的稀疏性,通过少量的观测值就可以实现对该信号的精确重构。贪婪类算法是压缩感知重构步骤中广泛应用的一类算法。该文主要对该类算法中典型的三种算法在存在噪声环境中进行了综合分析比较。首先从理论方面分析了三种算法,给出了实现过程;然后在不同稀疏度情况下,对三种贪婪算法重构性能进行综合比较。根据理论分析结果和仿真结果,得出相应的结论。
Compressive sensing is a novel signal sampling theory under the condition that the signals are sparse.In this case ,the small amount of signal values can be reconstructed accurately. Greedy algorithm is one class of the algorithms used most widely in CS signal reconstruction.In this paper, the three classic greedy algorithms are analyzed and compared theoretically in noise condition with different sparsity level,by the analysis and simulation result,the conclusion is obtained.
作者
冯俊杰
季立贵
FENG Jun-jie, JI Li-gui （School of Physics and Information Technology,Liu pan shui Normal University, Liupanshui 553004, China）
出处
《电脑知识与技术》
2014年第11期7351-7353,共3页
Computer Knowledge and Technology
基金
贵州省教育厅重点项目（黔教合KY字[2013]174）
贵州省教育厅科技创新人才支持计划项目（黔教合KY字[2013]146）
关键词
压缩感知
稀疏度
贪婪算法
信号重构
compressive sensing
sparsity
greedy algorithm
signal reconstruction
