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SUMMARY:Information-Theoretic Extensions of the Shannon-Nyquist Sampling T
 heorem - Guangyue Han (University of Hong Kong)
DTSTART:20180723T130000Z
DTEND:20180723T134500Z
UID:TALK108256@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>This talk will present information-theoretic extensions 
 of the classical Shannon-Nyquist sampling theorem and some of their applic
 ations. More specifically\, we consider a continuous-time white Gaussian c
 hannel\, which is typically formulated using a white Gaussian noise. A con
 ventional way for examining such a channel is the sampling approach based 
 on the Shannon-Nyquist sampling theorem\, where the original continuous-ti
 me channel is converted to an equivalent discrete-time channel\, to which 
 a great variety of established tools and methodology can be applied. Howev
 er\, one of the key issues of this scheme is that continuous-time feedback
  and memory cannot be incorporated into the channel model. It turns out th
 at this issue can be circumvented by considering the Brownian motion formu
 lation of a continuous-time white Gaussian channel. Nevertheless\, as oppo
 sed to the white Gaussian noise formulation\, a link that establishes the 
 information-theoretic connection between a continuous -time channel under 
 the Brownian motion formulation and its discrete-time counterparts has lon
 g been missing. This paper is to fill this gap by establishing causality-p
 reserving connections between continuous-time Gaussian feedback/memory cha
 nnels and their associated discrete-time versions in the forms of sampling
  and approximation theorems\, which we believe will help to contribute the
  further development of continuous-time information theory.<br></span><br>
 Related Links<ul><li><a target="_blank" rel="nofollow">https://arxiv.org/a
 bs/1704.02569</a></li></ul><br>
LOCATION:Seminar Room 1\, Newton Institute
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