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http://dx.doi.org/10.6109/jkiice.2013.17.8.1784

Sparse Signal Recovery with Parallel Orthogonal Matching Pursuit and Its Performances  

Park, Jeonghong (Department of Information and Communication Engineering, Gyeongsang National University)
Jung, Bang Chul (Department of Information and Communication Engineering, Gyeongsang National University)
Kim, Jong Min (Department of Mathematics and Computer Science, Korea Science Academy of KAIST)
Ban, Tae Won (Department of Information and Communication Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.8, 2013 , pp. 1784-1789 More about this Journal
Abstract
In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the orthogonal matching pursuit (OMP) which has been widely used as a greedy algorithm for sparse signal recovery. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the firest iteration, (2) the conventional OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP outperforms than the existing sparse signal recovery algorithms in terms of exact recovery ratio (ERR) for sparse pattern and mean-squared error (MSE) between the estimated signal and the original signal.
Keywords
Compressed sensing; Sparse signal recovery; Orthogonal matching pursuit; Detection; Mean squared error;
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