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CATEGORIES:Applied and Computational Analysis
SUMMARY:Compressive sampling - Emmanuel Candes (California
  Institute of Technology)
DTSTART;TZID=Europe/London:20080117T150000
DTEND;TZID=Europe/London:20080117T160000
UID:TALK8892AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/8892
DESCRIPTION:One of the central tenets of signal processing is 
 the Shannon/Nyquist sampling theory: the number of
  samples needed to reconstruct a signal without er
 ror is dictated by its\nbandwidth-the length of th
 e shortest interval which contains the\nsupport of
  the spectrum of the signal under study.  Very\nre
 cently\, an alternative sampling or sensing theory
  has emerged\nwhich goes against this conventional
  wisdom.  This theory allows\nthe faithful recover
 y of signals and images from what appear to\nbe hi
 ghly incomplete sets of data\, i.e. from far fewer
  data bits\nthan traditional methods use.  Underly
 ing this metholdology is a\nconcrete protocol for 
 sensing and compressing data\nsimultaneously.\n\nT
 his talk will present the key mathematical ideas u
 nderlying this\nnew sampling or sensing theory\, a
 nd will survey some of the most\nimportant results
 . We will argue that this is a robust\nmathematica
 l theory\; not only is it possible to recover sign
 als\naccurately from just an incomplete set of mea
 surements\, but it is\nalso possible to do so when
  the measurements are unreliable and\ncorrupted by
  noise. We will see that the reconstruction\nalgor
 ithms are very concrete\, stable (in the sense tha
 t they\ndegrade smoothly as the noise level increa
 ses) and practical\; in\nfact\, they only involve 
 solving very simple convex optimization\nprograms.
 \n\nAn interesting aspect of this theory is that i
 t has bearings on\nsome fields in the applied scie
 nces and engineering such as\nstatistics\, informa
 tion theory\, coding theory\, theoretical\ncompute
 r science\, and others as well.  If time allows\, 
 we will\ntry to explain these connections via a fe
 w selected examples.\n\n
LOCATION:MR14\, CMS
CONTACT:
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