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SUMMARY:A nonlinear approach to generalized sampling - Clarice Poon (CCA)
DTSTART:20130508T150000Z
DTEND:20130508T160000Z
UID:TALK44740@talks.cam.ac.uk
CONTACT:Martin Taylor
DESCRIPTION:One of the central problems of sampling theory is the reconstr
 uction of an \nimage or a signal from a collection of measurements. Typica
 lly\, this \nproblem may be modeled in a Hilbert space setting and measure
 ments are \ntaken with respect to some set of vectors\, such as some Fouri
 er basis. \nGeneralized sampling is a framework for obtaining reconstructi
 ons in \narbitrary spaces without constraints on the type of measurements.
  In my \ntalk\, I will present generalized sampling as an l^1 minimization
  problem \nand apply this framework to the reconstruction of wavelets coef
 ficients \nfrom Fourier samples. I will also briefly discuss some implicat
 ions of \ngeneralized sampling for the use of variable density sampling sc
 hemes in \ncompressed sensing.
LOCATION:MR14\, Centre for Mathematical Sciences
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