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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Information-Theoretic Extensions of the Shannon-Ny
quist Sampling Theorem - Guangyue Han (University
of Hong Kong)
DTSTART;TZID=Europe/London:20180723T140000
DTEND;TZID=Europe/London:20180723T144500
UID:TALK108256AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/108256
DESCRIPTION:This talk will present information-theoretic
extensions of the classical Shannon-Nyquist sampl
ing theorem and some of their applications. More s
pecifically\, we consider a continuous-time white
Gaussian channel\, which is typically formulated u
sing a white Gaussian noise. A conventional way fo
r examining such a channel is the sampling approac
h based on the Shannon-Nyquist sampling theorem\,
where the original continuous-time channel is conv
erted to an equivalent discrete-time channel\, to
which a great variety of established tools and met
hodology can be applied. However\, one of the key
issues of this scheme is that continuous-time feed
back and memory cannot be incorporated into the ch
annel model. It turns out that this issue can be c
ircumvented by considering the Brownian motion for
mulation of a continuous-time white Gaussian chann
el. Nevertheless\, as opposed to the white Gaussia
n noise formulation\, a link that establishes the
information-theoretic connection between a continu
ous -time channel under the Brownian motion formul
ation and its discrete-time counterparts has long
been missing. This paper is to fill this gap by es
tablishing causality-preserving connections betwee
n continuous-time Gaussian feedback/memory channel
s and their associated discrete-time versions in t
he forms of sampling and approximation theorems\,
which we believe will help to contribute the furth
er development of continuous-time information theo
ry.

Related Links

LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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