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Greedy Sparse Algorithms.pdf

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Preview of Greedy Sparse Algorithms
🔗 Source: inria.hal.science
📊 Size: 314 KB
👤 Author: Boris Mailhé, Bob L. Sturm, Mark D. Plumbley
⬇️ Downloads: 105

Summary

The behavior of greedy sparse representation algorithms on nested supports is studied, focusing on Orthogonal Matching Pursuit (OMP) and the General MP class. It is shown that OMP's optimality is not locally nested, but globally nested, meaning that if OMP can recover all s-sparse signals, it can also recover all s'-sparse signals with s' < s. A tighter version of Donoho and Elad's spark theorem is provided, allowing for the completion of Tropp's proof that sparse representation algorithms can only be optimal for all s-sparse signals if s is strictly lower than half the spark of the dictionary.

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Description

The behavior of greedy sparse representation algorithms on nested supports is studied, focusing on Orthogonal Matching Pursuit (OMP) and the General MP class.

Technical Information

  • File Format: PDF
  • File Size: 314 KB
  • Pages: 6
  • Language: EN
  • Author: Boris Mailhé, Bob L. Sturm, Mark D. Plumbley
  • Total Downloads: 105
  • Last Updated: 4 weeks ago

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