A Sparsity Adaptive Signal Reconstruction Algorithm

被引:0
|
作者
Li, Zhou [1 ]
Cui, Chen [1 ]
Yi, Renjie [1 ]
机构
[1] Elect Engn Inst, Hefei, Anhui, Peoples R China
来源
2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017) | 2017年
关键词
multipath matching pursuit; adaptive; regularized; retrospective tracing; PURSUIT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Aiming at the problem of sparse signal reconstruction when signal's sparsity is unknown in Compressive Sensing (CS), a sparsity adaptive signal reconstruction algorithm based on Multipath Matching Pursuit(MMP) is proposed. In the algorithm, comparing the minimum residual among residuals corresponding to candidate sets in each iteration with the threshold which is set in advance is the only factor to decide whether or not the reconstruction is completed, meanwhile the regularization criterion and the improved retrospective tracing theory are adopted to reduce the number of candidate sets in each iteration. The simulation results show that with no prior knowledge of signal's sparsity, the proposed algorithm has a good reconstruction effect with acceptable computation.
引用
收藏
页码:852 / 857
页数:6
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