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首页> 外文期刊>Signal Processing, IET >Block-sparse compressed sensing with partially known signal support via non-convex minimisation
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Block-sparse compressed sensing with partially known signal support via non-convex minimisation

机译：通过非凸最小化，具有部分已知信号支持的块稀疏压缩传感

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摘要

The mixed l2/lp (0 <; p ≤ 1) norm minimisation method with partially known support for recovering block-sparse signals is studied. The authors mainly extend this work on block-sparse compressed sensing by incorporating some known part of the block support information as a priori and establish sufficient restricted p-isometry property (p-RIP) conditions for exact and robust recovery. The authors' theoretical results show it is possible to recover the block-sparse signals via l2/lp minimisation from reduced number of measurements by applying the partially known support. The authors also derive a lower bound on necessary random Gaussian measurements for the p-RIP conditions to hold with high possibility. Finally, a series of numerical experiments are carried out to illustrate that fewer measurements with smaller p are needed to reconstruct the signal.
机译：研究了在部分已知的支持下恢复块稀疏信号的混合l2 / lp（0 <; p≤1）范数最小化方法。作者主要通过先验地结合块支持信息的一些已知部分，将这项工作扩展到块稀疏压缩感知上，并建立足够的受限p等轴测特性（p-RIP）条件，以实现精确而稳健的恢复。作者的理论结果表明，通过应用部分已知的支持方法，可以从减少的测量次数中通过L2 / Ip最小化来恢复块稀疏信号。作者还为p-RIP条件得出了必要的随机高斯测量值的下界，以保持较高的可能性。最后，进行了一系列数值实验，以说明重建信号所需的测量值较小且p较小。

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