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Open AccessArticle

A Matching Pursuit Algorithm for Backtracking Regularization Based on Energy Sorting

by Hanfei Zhang 1,*, Shungen Xiao 2,* and Ping Zhou 1
1
Information service and Information Research Center, Huaiyin Normal University, Huai’an 223700, China
2
School of Information Mechanical and Electrical Engineering, Ningde Normal University, Ningde 352100, China
*
Authors to whom correspondence should be addressed.
Symmetry 2020, 12(2), 231; https://doi.org/10.3390/sym12020231
Received: 9 December 2019 / Revised: 26 January 2020 / Accepted: 29 January 2020 / Published: 3 February 2020
(This article belongs to the Special Issue Selected Papers from IIKII 2019 conferences in Symmetry)
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. View Full-Text
Keywords: backtracking; energy sorting; atom screening backtracking; energy sorting; atom screening
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Zhang, H.; Xiao, S.; Zhou, P. A Matching Pursuit Algorithm for Backtracking Regularization Based on Energy Sorting. Symmetry 2020, 12, 231.

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