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A Simple Gaussian Measurement Bound for Exact Recovery of Block-Sparse Signals

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Listed:
  • Zhi Han
  • Jianjun Wang
  • Jia Jing
  • Hai Zhang

Abstract

We present a probabilistic analysis on conditions of the exact recovery of block-sparse signals whose nonzero elements appear in fixed blocks. We mainly derive a simple lower bound on the necessary number of Gaussian measurements for exact recovery of such block-sparse signals via the mixed norm minimization method. In addition, we present numerical examples to partially support the correctness of the theoretical results. The obtained results extend those known for the standard minimization and the mixed minimization methods to the mixed minimization method in the context of block-sparse signal recovery.

Suggested Citation

  • Zhi Han & Jianjun Wang & Jia Jing & Hai Zhang, 2014. "A Simple Gaussian Measurement Bound for Exact Recovery of Block-Sparse Signals," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-8, November.
    • Handle: RePEc:hin:jnddns:104709
    DOI: 10.1155/2014/104709
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    References listed on IDEAS

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    1. Ming Yuan & Yi Lin, 2006. "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 49-67, February.
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