Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring...

signal detection theory is called compressed sensing (or compressive sensing). The objective of compressed sensing is to recover high dimensional but...

arithmetic combinatorics, geometric combinatorics, probability theory, compressed sensing and analytic number theory. Tao was born to Chinese immigrant parents...

using the knowledge of the compressed signal and the measurement matrix. Mathematically, the recovery process in Compressed Sensing is finding the sparsest...

vector. This approach appears in the signal recovery framework called compressed sensing. Taxicab geometry can be used to assess the differences in discrete...

and Terence Tao and is used to prove many theorems in the field of compressed sensing. There are no known large matrices with bounded restricted isometry...

In communications technology, the technique of compressed sensing (CS) may be applied to the processing of speech signals under certain conditions. In...

signal are known (see § Sampling of non-baseband signals below and compressed sensing). In some cases (when the sample-rate criterion is not satisfied)...

In compressed sensing, the nullspace property gives necessary and sufficient conditions on the reconstruction of sparse signals using the techniques of...

statistician most well known for his contributions to the field of Compressed sensing and Statistical hypothesis testing. He is a professor of statistics...