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In this experiment, problem dimension is set to D=20, which is larger than existing studies [14, 15].
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In the first step of any design of experiment problems, the responses and their descriptions such as their types should be determined.
As in the first experiment, problems were presented in a predefined pseudorandomized sequence that was designed to balance rule and task familiarity across the 4 reasoning conditions.
We also depend on science and technology: hypotheses, experimenting, problem solving, testing, reviewing by committees of peers, and lots of revisions along the way.
This work solves an experiment design problem for a linear regression problem using a reduced order model.
The experiment design problem is cast as an optimal control problem, with experiment decision variables such as sampling times of response variables, time-varying and time-invariant external controls, experiment duration, and initial conditions.
On the basis of a mathematical model of the experimental system, the optimal experiment design problem was solved as an optimal control problem.
An optimal experiment design problem invoked by the Cramér-Rao Inequality is applied to the problem of quantum state tomography.
In this paper, we solve the related experiment design problem.
In this paper we examine the application of a recently proposed idea of 'variable robustness' to the experiment design problem.
We illustrate the technique by solving an optimal experiment design problem for a fed-batch bioreactor benchmark case study.
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