An Improved Stagewise Orthogonal Matching Pursuit-Recursive Algorithm for Power Quality Signal Reconstruction

2019 ◽  
Author(s):  
Binghui Han ◽  
Hui Jiang
Keyword(s):  
Power Quality ◽  
Matching Pursuit ◽  
Recursive Algorithm ◽  
Signal Reconstruction ◽  
Orthogonal Matching Pursuit ◽  
Quality Signal ◽  
Stagewise Orthogonal Matching Pursuit

An Optimised Signal Reconstruction Algorithm for Compressed Sensing

2013 ◽  
Vol 333-335 ◽  
pp. 567-571
Author(s):  
Zhao Shan Wang ◽  
Shan Xiang Lv ◽  
Jiu Chao Feng ◽  
Yan Sheng ◽  
Zhong Liang Wu ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Small Proportion ◽  
Matching Pursuit ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Orthogonal Matching Pursuit ◽  
Signal Recovery ◽  
Successful Recovery ◽  
Stagewise Orthogonal Matching Pursuit ◽  
Convergence Of Algorithm

Signal recovery is a key issue in compressed sensing field. A new greedy reconstruction algorithm termed Optimised Stagewise Orthogonal Matching Pursuit (OSOMP) is proposed, which is an improved version for Stagewise Orthogonal Matching Pursuit (StOMP). In preselection step, OSOMP chooses several coordinates with a calculated threshold to accelerate the convergence of algorithm. In following pruning step, a small proportion of selected coordinates are discarded according to the amplitude of estimated signal, thus most false discovered coordinates can be swept away. Experimental results show that in OSOMP, the scale of estimated support can be controlled very well, and the successful recovery rate is also much higher than that in StOMP.

scholarly journals A Matching Pursuit Algorithm for Backtracking Regularization Based on Energy Sorting

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 231 ◽  
Author(s):  
Hanfei Zhang ◽  
Shungen Xiao ◽  
Ping Zhou
Keyword(s):  
Energy Distribution ◽  
Matching Pursuit ◽  
Signal Reconstruction ◽  
Selection Criterion ◽  
Critical Factor ◽  
Maximum Energy ◽  
Orthogonal Matching Pursuit ◽  
Support Set ◽  
Reconstruction Efficiency ◽  
Matching Pursuit Algorithm

The signal reconstruction quality has become a critical factor in compressed sensing at present. This paper proposes a matching pursuit algorithm for backtracking regularization based on energy sorting. This algorithm uses energy sorting for secondary atom screening to delete individual wrong atoms through the regularized orthogonal matching pursuit (ROMP) algorithm backtracking. The support set is continuously updated and expanded during each iteration. While the signal energy distribution is not uniform, or the energy distribution is in an extreme state, the reconstructive performance of the ROMP algorithm becomes unstable if the maximum energy is still taken as the selection criterion. The proposed method for the regularized orthogonal matching pursuit algorithm can be adopted to improve those drawbacks in signal reconstruction due to its high reconstruction efficiency. The experimental results show that the algorithm has a proper reconstruction.

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