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A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit

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Abstract

We consider the block orthogonal multi-matching pursuit (BOMMP) algorithm for the recovery of block sparse signals. A sharp condition is obtained for the exact reconstruction of block K-sparse signals via the BOMMP algorithm in the noiseless case, based on the block restricted isometry constant (block-RIC). Moreover, we show that the sharp condition combining with an extra condition on the minimum ℓ2 norm of nonzero blocks of block K-sparse signals is sufficient to ensure the BOMMP algorithm selects at least one true block index at each iteration until all true block indices are selected in the noisy case. The significance of the results we obtain in this paper lies in the fact that making explicit use of block sparsity of block sparse signals can achieve better recovery performance than ignoring the additional structure in the problem as being in the conventional sense.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 11271050 and 11371183). The authors thank the referees for their valuable comments that improve the presentation of this paper.

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Authors and Affiliations

  1. Institute of Applied Physics and Computational Mathematics, Beijing, 100088, China

    WenGu Chen

  2. Graduate School, China Academy of Engineering Physics, Beijing, 100088, China

    HuanMin Ge

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  1. WenGu Chen
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  2. HuanMin Ge
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Correspondence to WenGu Chen.

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Chen, W., Ge, H. A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit. Sci. China Math. 60, 1325–1340 (2017). https://doi.org/10.1007/s11425-016-0448-7

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