Compressed Sensing: Algorithms and Applications

Anna Gilbert
University of Michigan

ABSTRACT:
Compressed Sensing is a new paradigm for acquiring the compressible
signals that arise in many applications. These signals can be
approximated using an amount of information much smaller than the
nominal dimension of the signal. Traditional approaches acquire the
entire signal and process it to extract the information. The new
approach acquires a small number of nonadaptive linear measurements of
the signal and uses sophisticated algorithms to determine its
information content. Emerging technologies can compute these general
linear measurements of a signal at unit cost per measurement.