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SUMMARY:The geometry of optimal experiment design for vector-valued Ornste
 in-Uhlenbeck processes. - Mohamed-Ali Belabbas (University of Illinois at 
 Urbana-Champaign)
DTSTART:20161124T140000Z
DTEND:20161124T150000Z
UID:TALK69149@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Ornstein-Uhlenbeck processes are commonly used as models in en
 gineering\, biology and finance. Consider the estimation of the state of s
 uch processes from linear\, noisy measurements\;&nbsp\;the Kalman filter i
 s known to be the minimum mean square error estimator when the measurement
  noise is Gaussian. We address here how to design the measurements that mi
 nimize the error afforded by the Kalman filter. This problem of optimal ex
 periment design\, which is almost as old as the Kalman filter itself\, &nb
 sp\;is however&nbsp\;not convex. As a consequence\, many ad hoc methods ha
 ve been used over the years to solve it. We show in this talk how a geomet
 ric approach allows us to characterize and obtain the optimal designs exac
 tly. This optimal design yields the lowest possible estimation error from 
 linear measurements with a fixed signal to noise ratio.&nbsp\;   <br><br><
 br>
LOCATION:Seminar Room 2\, Newton Institute
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