A NEW ALGORITHM ON HIERARCHICAL SPARSE SIGNAL RECONSTRUCTION

被引:0
|
作者
Gao, Han [1 ]
Zhang, Hao [1 ]
Wang, Xiqin [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
来源
2015 IEEE CHINA SUMMIT & INTERNATIONAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING | 2015年
关键词
Hierarchical sparsity; Signal Reconstruction; Compressive Sensing; ORTHOGONAL MATCHING PURSUIT; RECOVERY;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Reconstructing signals that have a sparse representation has been studied in the recent years. However, most of the work dealing with this problem requires a low-coherent dictionary matrix. This article presents a novel procedure for sparse signal reconstruction with high coherent dictionary by partitioning the dictionary in the preprocessing step and addressing the reconstruction of hierarchical sparse signals via a new matching pursuit algorithm. We analyse the performance of the proposed algorithm in the noiseless case and show that given the same conditions as required for OMP, it achieves at least the same reconstruction performance as OMP. Numerical simulation and experimental results show that by exploiting the hierarchical sparse structure of the signal, the proposed method outperforms those traditional methods.
引用
收藏
页码:118 / 122
页数:5
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