## 留言板

 引用本文: 欧国建, 蒋清平, 秦长春. 基于子空间的三阶多项式相位信号快速稀疏分解算法[J]. 电子与信息学报, 2018, 40(3): 648-655.
OU Guojian, JIANG Qingping, QING Changchun. A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace[J]. Journal of Electronics and Information Technology, 2018, 40(3): 648-655. doi: 10.11999/JEIT170593
 Citation: OU Guojian, JIANG Qingping, QING Changchun. A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace[J]. Journal of Electronics and Information Technology, 2018, 40(3): 648-655.

## A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace

Funds:

The project of ChongQing municipal education Commission (KJ1602909, KJ1503004), The National Natural Science Foundation of China (61371164), Intelligent Robot Techndogy Research Center of Electronic Engineering (XJPT201705)

• 摘要: 针对稀疏分解冗余字典中原子数量庞大的缺点，该文提出一种三阶多项式相位信号的快速稀疏分解算法。该算法根据三阶多项式相位信号的特点，把原有信号变换成两个子空间信号，并根据这两个子空间信号构建相应的冗余字典，然后采用正交匹配追踪法来完成其稀疏分解，最后利用稀疏分解原理完成原有信号的稀疏分解。该算法把原有信号变换成两个不同子空间信号，构建了两个不同的冗余字典，对比采用一个冗余字典库，这种采用两个冗余字典的算法大大减少了原子数量，并且通过快速傅里叶变换，在一个冗余字典进行稀疏分解时，同时找到另一个冗余字典中的最匹配的原子。因此该算法通过减少原子数量和采用快速傅里叶变换大大加快了稀疏分解速度。实验结果表明，相比于采用Gabor原子构建的冗余字典，采用匹配追踪算法与遗传算法及最近提出的基于调制相关划分的快速稀疏分解，它的稀疏分解速度更快，并且具有更好的收敛性。
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##### 出版历程
• 收稿日期:  2017-06-21
• 修回日期:  2017-11-29
• 刊出日期:  2018-03-19

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