| 压缩感知重构算法在稀疏信号恢复中的应用 |
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| 引用本文： | 宋晓霞,李勇.压缩感知重构算法在稀疏信号恢复中的应用[J].山西大同大学学报（自然科学版）,2013(5):1-3,9. |
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| 作者姓名： | 宋晓霞 李勇 |
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| 作者单位： | 山西大同大学数学与计算机科学学院 |
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| 基金项目： | 国家自然科学基金资助项目[61307121] |
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| 摘 要： | 阐述了压缩感知理论产生的背景、基本原理和应用方式，研究了两类压缩感知重构算法的重构思想和方法，并将两类重构算法的典型算法正交匹配追踪和基追踪应用于稀疏信号的重构。结果表明：对于无噪观测和含较小噪声的观测，正交匹配追踪算法从重构频率和重构时间两方面显示出更好的性能。
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| 关 键 词： | 压缩感知 重构算法 稀疏信号 贪婪追踪算法 凸松弛算法 |
Application of Sparse Signal Restoration via Reconstruction Algorithms of Compressed Sensing |
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| SONG Xiao-xia;LI Yong.Application of Sparse Signal Restoration via Reconstruction Algorithms of Compressed Sensing[J].Journal of Shanxi Datong University(Natural Science Edition),2013(5):1-3,9. |
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| Authors: | SONG Xiao-xia;LI Yong |
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| Institution: | SONG Xiao-xia;LI Yong;School of Mathematics and Computer Science,Shanxi Datong University; |
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| Abstract: | This paper illustrates the background, the basic principle and application of compressed sensing theory. Two kinds of reconstruction algorithms are studied from the idea and method. And then typical algorithms including orthogonal matching pursuit and basis pursuit are applied to the reconstruction of sparse signals. The results suggest that orthogonal matching pursuit algorithm shows better performances from the two aspects of reconstruction frequency and time for compressive measurements without noise or with small noise. |
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| Keywords: | compressed sensing reconstruction algorithm sparse signal greedy pursuit algorithm convex relaxation algorithm |
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