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A Block Fixed Point Continuation Algorithm for Block-Sparse Reconstruction

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3 Author(s)
Jian Zou ; Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China ; Yuli Fu ; Shengli Xie

Block-sparse reconstruction, which arises from the reconstruction of block-sparse signals in structured compressed sensing, is generally considered difficult to solve due to the mixed-norm structure. In this letter, we propose an algorithm for reconstructing block-sparse signals, that is an extension of fixed point continuation in block-wise case by incorporating block coordinate descent technique. We also apply our algorithm to multiple measurement vector reconstruction, that is a special case of block-sparse reconstruction and can be used in magnetic resonance imaging reconstruction. Numerical results show the validity of our algorithm for both synthetic and real-world data.

Published in:

Signal Processing Letters, IEEE  (Volume:19 ,  Issue: 6 )