Introduction - If you have any usage issues, please Google them yourself
A classic article on compressed sensing, compressive sensing (Compressed sensing, referred to as CS, also known as Compressive sampling) different from the modern theory of the Nyquist sampling theorem, which states: the use of a random measurement matrix can be sparse or compressible high-dimensional signal projected to low dimensional space, and then use a small amount of projection by solving an optimization problem to be sparse with high probability to reconstruct the original signal, and prove that random projection of the original sparse signal contains enough information.