Sparse Sampling of Signal Innovations

  title={Sparse Sampling of Signal Innovations},
  author={Thierry Blu and P.-L. Dragotti and Martin Vetterli and Pina Marziliano and Lionel Coulot},
  journal={IEEE Signal Processing Magazine},
Sparse sampling of continuous-time sparse signals is addressed. In particular, it is shown that sampling at the rate of innovation is possible, in some sense applying Occam's razor to the sampling of sparse signals. The noisy case is analyzed and solved, proposing methods reaching the optimal performance given by the Cramer-Rao bounds. Finally, a number of applications have been discussed where sparsity can be taken advantage of. The comprehensive coverage given in this article should lead to… CONTINUE READING
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