University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Optimal input signals for parameter estimation in distributed-parameter systems

Optimal input signals for parameter estimation in distributed-parameter systems

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Mustapha Amrani.

Design and Analysis of Experiments

In the first part of the lecture we recall classical results on selecting optimal input signals for parameter estimation in systems with temporal (or spatial) dynamics only and their generalizations to unbounded signals. As a motivation for studying input signals, which can influence our system both in space and in time, we provide several examples of new techniques emerged in high energy lasers and in micro- and nano-technologies. We also mention an increasing role of cameras as sensors. Then, we discuss extensions of optimality conditions for input signals, trying to reveal an interplay between their spatial and temporal behavior. We concentrate on open loop input signals for linear systems, described by partial differential equations (PDE) or their Green’s functions. Finally, we sketch the following open problems: (i) simultaneous optimization of sensor positions and input signals, (ii) experiment design for estimating spatially varying coefficients of PDEs.

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity