Compressed sensing
From Wikipedia, the free encyclopedia
Compressed sensing, or compressive sensing, is a statistical technique for data acquisition and estimation that aims to sample signals sparsely in transform domains. The sparse samples may be decoded into (i.e., used to estimate) the original signal under certain conditions. The method was originally proposed by Emmanuel Candes and Terence Tao.
