Design of Experiments Using Uncertainty Information

Abstract
The process of parameter estimation and the estimated parameters are affected not only by measurement noise, which is present during any experiment, but also by uncertainties in the parameters of the model used to describe the system. This paper describes a method to optimize the design of an experiment to deduce the maximum information during the inverse problem of parameter estimation in the presence of uncertainties in the model parameters. It is shown that accounting for these uncertainties affects the optimal locations of the sensors.

This publication has 12 references indexed in Scilit: