Compressed Sensing: How sharp is the Restricted Isometry Property

  title={Compressed Sensing: How sharp is the Restricted Isometry Property},
  author={Jeffrey D. Blanchard and Coralia Cartis and Jared Tanner},
  journal={SIAM Review},
Compressed sensing (CS) seeks to recover an unknown vector with N entries by making far fewer than N measurements; it posits that the number of CS measurements should be comparable to the information content of the vector, not simply N . CS combines directly the important task of compression with the measurement task. Since its introduction in 2004 there have been hundreds of papers on CS, a large fraction of which develop algorithms to recover a signal from its compressed measurements. Because… CONTINUE READING
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