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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Balanced model order reduction for linear systems
driven by L&\;eacute\;vy noise - Melina Freitag
(University of Bath)
DTSTART;TZID=Europe/London:20180618T110000
DTEND;TZID=Europe/London:20180618T130000
UID:TALK106762AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/106762
DESCRIPTION:When solving linear stochastic differential equati
ons numerically\, usually a high order spatial dis
cretisation is used. Balanced truncation (BT) is a
well-known projection technique in the determinis
tic framework which reduces the order of a control
system and hence reduces computational complexity
. We give an introduction to model order reduction
(MOR) by BT and then consider a differential equa
tion where the control is replaced by a noise term
. We provide theoretical tools such as stochastic
concepts for reachability and observability\, whic
h are necessary for balancing related MOR of linea
r stochastic differential equations with additive
L'\;evy noise. Moreover\, we derive error bound
s for BT and provide numerical results for a speci
fic example which support the theory. This is join
t work with Martin Redmann (WIAS Berlin).
LOCATION:Seminar Room 2\, Newton Institute
CONTACT:info@newton.ac.uk
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