| 一种新的基于压缩感知理论的稀疏信号重构算法 |
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| 引用本文： | 刘哲.一种新的基于压缩感知理论的稀疏信号重构算法[J].光电子．激光,2011(2):292-296. |
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| 作者姓名： | 刘哲 |
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| 作者单位： | 西北工业大学理学院; |
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| 基金项目： | 国家自然科学基金资助项目(60776795,61071170); 教育部新世纪优秀人才支持计划资助项目 |
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| 摘 要： | 针对基于l1范数优化的稀疏信号重构算法需要的观测样本数较多,本文以lp范数最小化为目标,结合传统的罚函数(PF)优化思想,给出了基于PF的lp范数迭代重构算法,需要的观测样本数大大低于基于l1范数的优化计算需求,并通过数值实验表明该算法对稀疏信号具有较优的重构效果.
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| 关 键 词： | 稀疏信号 压缩感知(CS) lp范数 信号重构 |
Novel sparse signal reconstruction algorithm based on compressed sensing theory |
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| LIU Zhe.Novel sparse signal reconstruction algorithm based on compressed sensing theory[J].Journal of Optoelectronics·laser,2011(2):292-296. |
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| Authors: | LIU Zhe |
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| Affiliation: | (School of Science,Northwestern Polytechnical University,Xi′an 710129,China) |
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| Abstract: | Reconstruction of sparse signals is an important issue in compressed sensing.Typical algorithms for sparse signals are based on l1-norm optimization,which need more measurements.With minimizing lp-norm as the goal,combined with traditional penalty function optimization method,an iterative reconstruction algorithm for lp-norm optimization based on penalty function was proposed,which needed far less measurements than l1-norm optimization.Numerical results show that the proposed algorithm has good performance ... |
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| Keywords: | sparse signal compressed sensing(CS) lp-norm signal reconstruction |
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