| 引用本文: | 张茜,郭金库,余志勇,等.使用小波分层连通树结构的压缩信号重构.[J].国防科技大学学报,2014,36(5):87-92.[点击复制] |
| ZHANG Qian,GUO Jinku,YU Zhiyong,et al.Compressive signal reconstruction using a hierarchical wavelet connected tree[J].Journal of National University of Defense Technology,2014,36(5):87-92[点击复制] |
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| 使用小波分层连通树结构的压缩信号重构 |
| 张茜, 郭金库, 余志勇, 刘光斌 |
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(第二炮兵工程大学， 陕西 西安 710025)
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| 摘要: |
| 基于小波树模型的压缩感知可以通过较少的观测量得到鲁棒的信号重构，但采用最优树逼近时,则存在复杂度大的问题。在证明分层后的小波树仍然具备连通树性质的基础上，提出了基于小波分层连通树结构的压缩重构算法，在与原观测量一致的情况下，保证了重构精度并且提高了重构效率。实验结果表明，改进算法相对于原算法在处理大尺度数据时，效率有明显的改善。 |
| 关键词: 压缩感知 信号重构 小波树模型 分层连通树 |
| DOI：10.11887/j.cn.201405015 |
| 投稿日期：2014-01-24 |
| 基金项目:国家自然科学基金资助项目（61201120） |
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| Compressive signal reconstruction using a hierarchical wavelet connected tree |
| ZHANG Qian, GUO Jinku, YU Zhiyong, LIU Guangbin |
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(The Second Artillery Engineering University, Xi’an 710025, China)
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| Abstract: |
| The model-based compressive sensing (CS) dictated that robust signal reconstruction was possible to obtain from fewer measurements, but the computational complexity of this approach was large while using the optimal tree approximation with wavelets. Based on the testified result that the wavelet hierarchical tree was still connected, the model-based wavelet hierarchical connected tree CS algorithm， was proposed. The proposed algorithm which has the equivalent measurements with that of model-based CS can enhance the signal-reconstruction efficiency and guarantee the signal-reconstruction accuracy. Numerical simulations demonstrate the validity of the new algorithm. Furthermore, the proposed algorithm has a distinct advantage when dealing with the mass of data. |
| Keywords: compressive sensing signal reconstruction wavelet tree hierarchical connected tree |
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