Compressed Sensing or Compressive Sensing is about acquiring and recovering a sparse signal in the most efficient way possible (subsampling) with the help of an incoherent projecting basis. Unlike traditional sampling methods, Compressed Sensing provides a new framework for acquiring sparse signals in a mutiplexed manner. The main theoretical findings in this recent field have mostly centered on how many multiplexed measurements are necessary to reconstruct the original signal and the attendant nonlinear reconstruction techniques needed to demultiplex these signals. Another equally important thrust in the field has been the actual building of sensing hardware that could produce directly the multiplexed signals.
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