Title :
A new derivative free method for optimal experimental design utilizing a maximum a posteriori update
Author :
Kawohl, M. ; Heine, T.
Author_Institution :
Meas. & Control Group, Tech. Univ. Berlin, Berlin, Germany
Abstract :
We present a new derivative free method for the calculation of the information content of a planned experiment in optimal experimental design (OED). It is shown that in case of a mathematical model that is linear in the model parameters the new approach yields the same result as a calculation with the Fisher Information Matrix (FIM). The new algorithm is derived from a maximum a posteriori (MAP) update. The needed statistical moments of the planned trajectory are calculated using a derivative free approach, the Unscented Transformation (UT). The algorithm is demonstrated using a simple, but very instructive biological growth model.
Keywords :
covariance matrices; design of experiments; maximum likelihood estimation; optimisation; FIM; Fisher information matrix; MAP update; OED; UT; biological growth model; covariance matrix; derivative free method; information content; mathematical model; maximum a posteriori update; model parameters; optimal experimental design; planned experiment; planned trajectory; statistical moments; unscented transformation; Approximation methods; Biological system modeling; Covariance matrices; Mathematical model; Maximum likelihood estimation; Substrates; Trajectory; Maximum a posteriori update; Optimal experimental design; Unscented Transformation;
Conference_Titel :
Control Conference (ECC), 2007 European
Conference_Location :
Kos
Print_ISBN :
978-3-9524173-8-6
