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SUMMARY:Generalized Sampling and Infinite-Dimensional Compressed Sensing -
  Hansen\, A (University of Cambridge)
DTSTART:20110826T134500Z
DTEND:20110826T143000Z
UID:TALK32504@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:I will discuss a generalization of the Shannon Sampling Theore
 m that allows for reconstruction of signals in arbitrary bases (and frames
 ). Not only can one reconstruct in arbitrary bases\, but this can also be 
 done in a completely stable way. When extra information is available\, suc
 h as sparsity or compressibility of the signal in a particular basis\, one
  may reduce the number of samples dramatically. This is done via Compresse
 d Sensing techniques\, however\, the usual finite-dimensional framework is
  not sufficient. To overcome this obstacle I'll introduce the concept of I
 nfinite-Dimensional Compressed Sensing.\n
LOCATION:Seminar Room 1\, Newton Institute
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