| 基于近似l0范数的稳健稀疏重构算法 |
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| 引用本文： | 王军华,黄知涛,周一宇,王丰华.基于近似l0范数的稳健稀疏重构算法[J].电子学报,2012,40(6):1185-1189. |
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| 作者姓名： | 王军华 黄知涛 周一宇 王丰华 |
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| 作者单位： | 1. 国防科学技术大学电子科学与工程学院,湖南长沙410073;二炮士官学校,山东青州262500
2. 国防科学技术大学电子科学与工程学院,湖南长沙,410073 |
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| 基金项目： | 国家自然科学基金，新世纪优秀人才支持计划资助项目 |
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| 摘 要： | 针对测量值受噪声污染的稀疏重构问题,本文提出了稳健近似l0范数最小化算法.该算法首先利用反正切函数近似l0范数,然后建立基于近似l0范数的含噪稀疏重构模型,最后通过拟牛顿法求解该模型,并分析了算法的收敛性.数值仿真表明,本文提出的算法重构稀疏向量时需要较少的测量值,且具有较高的计算精度.
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| 关 键 词： | 压缩感知 稀疏重构 基追踪 平滑l0范数 |
| 收稿时间： | 2011-05-20 |
Robust Sparse Recovery Based on Approximate l0 Norm |
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| WANG Jun-hua
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HUANG Zhi-tao
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ZHOU Yi-yu
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WANG Feng-hua.Robust Sparse Recovery Based on Approximate l0 Norm[J].Acta Electronica Sinica,2012,40(6):1185-1189. |
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| Authors: | WANG Jun-hua HUANG Zhi-tao ZHOU Yi-yu WANG Feng-hua |
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| Affiliation: | 1(1.School of Electronic Science and Engineering,NUDT,Changsha,Hunan 410073,China;2.The Second Artillery Petty Officer School,Qingzhou,Shandong 262500,China) |
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| Abstract: | For the problem of recovering sparse vector with noisy measurements,robust approximate l0 norm minimization algorithm is proposed.Firstly,l0 norm is approximately expressed by arctan function.Secondly,the model of sparse recovery in the present of noise is constructed based on approximate l0 norm.Finally,the model is solved by quasi-Newton method to estimate sparse vector.Simulation results show that our algorithm needs fewer measurements and provides the better accuracy than the existing methods. |
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| Keywords: | compressed sensing sparse recovery basis pursuit smoothed l0 norm |
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