| 压缩感知稀疏信号重构算法研究 |
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| 引用本文： | 冯俊杰,季立贵.压缩感知稀疏信号重构算法研究[J].大众科技,2014(10):1-2. |
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| 作者姓名： | 冯俊杰 季立贵 |
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| 作者单位： | 六盘水师范学院,贵州 六盘水,553004 |
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| 基金项目： | 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)。 |
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| 摘 要： | 压缩感知理论是利用信号的稀疏性,采用重构算法通过少量的观测值就可以实现对该信号的精确重构。SL0（Smoothed l0）算法是基于l0范数的稀疏信号重构算法,通过控制参数逐步逼近最优解。针对平滑函数的选取问题,文章提出一种新的平滑函数序列近似l0范数,实现稀疏信号的精确重构。仿真结果表明,在相同实验条件下文章算法较传统算法有着较高的重构概率。
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| 关 键 词： | 压缩感知 平滑函数 l0范数 信号重构 |
Study on performance of sparse signal in compressive sensing |
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| Abstract: | 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.SL0（Smoothed l0） is a reconstruction algorithm based on l0 norm to get the optimal solution by changing parameters. In order to choose an approprite sequence of smoothed functions, we propose a new reconstruction algorithm based a new smoothed function which can get accurate reconstructon. Experimental results show that the proposed algorithm has better probability of reconstructon than other traditional algorithm. |
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| Keywords: | Compressive sensing smoothed function l0norm signal reconstruction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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