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MEMBERS OF RESEARCH CENTER
Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Lectures and Presetations
Dynamic Systems Identification with Gaussian Process Models
Lecturer:
Kocijan J.
From:
Oct. 27 2009 2:00PM
To:
Oct. 27 2009 4:00PM
Place:
místnost č. 474, ÚTIA AV ČR
Description:
Different models can be used for nonlinear dynamic
systems identification and the Gaussian process model is a
relatively new option with several interesting features:
model predictions contain the measure of confidence, the
model has a small number of training parameters and
facilitated structure determination, an different
possibilities of including prior knowledge exist.
In the presentation a basic principle of modeling with
Gaussian process models will be given and a case study of
dynamic system identification presented.
systems identification and the Gaussian process model is a
relatively new option with several interesting features:
model predictions contain the measure of confidence, the
model has a small number of training parameters and
facilitated structure determination, an different
possibilities of including prior knowledge exist.
In the presentation a basic principle of modeling with
Gaussian process models will be given and a case study of
dynamic system identification presented.
Contact person:
Within the event:
Pravidelný seminář Rozhodování a řízení za neurčitosti. (Contact person: Miroslav Kárný)