Journal of Systems Engineering and Electronics ›› 2013, Vol. 24 ›› Issue (4): 579-585.doi: 10.1109/JSEE.2013.00067

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Maximal-minimal correlation atoms algorithm for sparse recovery

Wei Gan*, Luping Xu, and Hua Zhang   

  1. School of Electronic Engineering, Xidian University, Xi’an 710071, China
  • Online:2013-08-21 Published:2010-01-03


A new iterative algorithm is proposed to reconstruct an unknown sparse signal from a set of projected measurements. Unlike existing greedy pursuit methods which only consider the atoms having the highest correlation with the residual signal, the proposed algorithm not only considers the higher correlation atoms but also reserves the lower correlation atoms with the residual signal. In the lower correlation atoms, only a few are correct which usually impact the reconstructive performance and decide the reconstruction dynamic range of greedy pursuit methods. The others are redundant. In order to avoid redundant atoms impacting the reconstructive accuracy, the Bayesian pursuit algorithm is used to eliminate them. Simulation results show that the proposed algorithm can improve the reconstructive dynamic range and the reconstructive accuracy. Furthermore, better noise immunity compared with the existing greedy pursuit methods can be obtained.