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11 October 2019 Sparse signal reconstruction via expanded subspace pursuit
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Abstract

Due to their low computational complexity, greedy pursuit algorithms are widely used in sparse signal reconstruction. An improved greedy iterative algorithm, called the expanded subspace pursuit, is proposed. By incorporating a simple backtracking technique, the proposed algorithm removes the mismatching atoms to refine the estimated support set effectively. Furthermore, the proposed algorithm can achieve blind sparse reconstruction even without the prior of the sparsity degree. Compared with other greedy algorithms, the proposed algorithm exhibits superior reconstruction accuracy and lower computational complexity. Finally, numerical results are presented to demonstrate the validity of the proposed algorithm.

© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2019/$28.00 © 2019 SPIE
Xiaodong Han, Guanghui Zhao, Xiaoming Li, Ting Shu, and Wenxian Yu "Sparse signal reconstruction via expanded subspace pursuit," Journal of Applied Remote Sensing 13(4), 046501 (11 October 2019). https://doi.org/10.1117/1.JRS.13.4.046501
Received: 26 March 2019; Accepted: 19 September 2019; Published: 11 October 2019
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