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CATEGORIES:Statistics
SUMMARY:Compressed sensing for the sparse Radon transform
- Giovanni Alberti (University of Genova)
DTSTART;TZID=Europe/London:20240216T140000
DTEND;TZID=Europe/London:20240216T150000
UID:TALK209551AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/209551
DESCRIPTION:Compressed sensing allows for the recovery of spar
se signals from a limited number of measurements\,
which is proportional - up to logarithmic factors
- to the sparsity of the unknown signal. The clas
sical theory mostly considers either random linear
measurements or subsampled isometries. In particu
lar\, the case with the subsampled Fourier transfo
rm finds applications to undersampled magnetic res
onance imaging. In this talk\, I will show how the
theory of compressed sensing can also be rigorous
ly applied to the sparse Radon transform\, in whic
h only a finite number of angles are considered. O
ne of the main novelties consists in the fact that
the Radon transform is associated to an ill-posed
inverse problem\, and the result follows from a n
ew theory of compressed sensing for abstract inver
se problems.
LOCATION:MR12\, Centre for Mathematical Sciences
CONTACT:Dr Sergio Bacallado
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