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1312.3968.pdf
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🔗 Source: arxiv.org
📊 Size: 159 KB
📄 Pages: 5 pages
⬇️ Downloads: 34

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The authors propose a novel approach to cosparse analysis compressive sensing (CS) based on the generalized approximate message passing (GAMP) algorithm, which works with a wide range of analysis operators and regularizers. They also propose a novel ℓ0-like soft-thresholder based on MMSE denoising for a spike-and-slab distribution with an infinite-variance slab. Numerical demonstrations on synthetic and practical datasets demonstrate advantages over existing AMP-based, greedy, and reweighted-ℓ1 approaches. The proposed method facilitates both MAP and (approximate) MMSE estimation of the signal in a computationally efficient manner, with a computational complexity of O(DN) for generic analysis operators or O(N log N) when the measurement and analysis operators have fast implementations.

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The authors propose a novel approach to cosparse analysis compressive sensing (CS) based on the generalized approximate message passing (GAMP) algorithm, which...

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  • File Format: PDF
  • File Size: 159 KB
  • Pages: 5
  • Language: EN
  • Total Downloads: 34
  • Last Updated: 1 week ago

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