From Denoising to Compressed Sensing

@article{Metzler2016FromDT,
  title={From Denoising to Compressed Sensing},
  author={Christopher A. Metzler and Arian Maleki and Richard G. Baraniuk},
  journal={IEEE Transactions on Information Theory},
  year={2016},
  volume={62},
  pages={5117-5144}
}
A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several decades, and as a result, todays denoisers can effectively remove large amounts of additive white Gaussian noise. A compressed sensing (CS) reconstruction algorithm seeks to recover a structured signal acquired using a small number of randomized measurements. Typical CS reconstruction algorithms can be cast as iteratively estimating a… CONTINUE READING
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