Sparse Signal Recovery Using A Tree Search 


Vol. 39,  No. 12, pp. 756-763, Dec.  2014


PDF
  Abstract

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

J. Lee and B. Shim, "Sparse Signal Recovery Using A Tree Search," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 756-763, 2014. DOI: .

[ACM Style]

Jaeseok Lee and Byonghyo Shim. 2014. Sparse Signal Recovery Using A Tree Search. The Journal of Korean Institute of Communications and Information Sciences, 39, 12, (2014), 756-763. DOI: .

[KICS Style]

Jaeseok Lee and Byonghyo Shim, "Sparse Signal Recovery Using A Tree Search," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 756-763, 12. 2014.