Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries

@article{Davenport2013SignalSC,
  title={Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries},
  author={Mark A. Davenport and Deanna Needell and Michael B. Wakin},
  journal={IEEE Transactions on Information Theory},
  year={2013},
  volume={59},
  pages={6820-6829}
}
Compressive sensing (CS) has recently emerged as a powerful framework for acquiring sparse signals. The bulk of the CS literature has focused on the case where the acquired signal has a sparse or compressible representation in an orthonormal basis. In practice, however, there are many signals that cannot be sparsely represented or approximated using an orthonormal basis, but that do have sparse representations in a redundant dictionary. Standard results in CS can sometimes be extended to handle… CONTINUE READING
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