Sparse sampling of signal innovations: Theory, algorithms, and performance bounds

A recent investigation on sparse sampling of continuous-time sparse signals has showed that sampling at the rate of innovation is possible, in some sense applying Occam's razor to the sampling of sparse signals. In addition, the noisy case has been solved after analysis, proposing methods reaching the optimal performance given by the Cramer-Rao bounds.