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Using any of these bases to approximate the input signal generates approximation error.
Used meta-model to analyze approximation error.
This leads to a consistently lower overall approximation error.
The approximation error of initial data is analyzed.
Approximation error variance was analyzed for various approximation ranges.
In this paper, we present algorithms for computing oblivious equilibrium and for bounding approximation error.
The approximation error can be controlled by an error estimation.
This error bound is determined by the approximation error of the estimation for the optimal cost and the approximation error of the controller function estimator.
Moreover, to relax the requirement for the bound of approximation error, an error estimation mechanism is investigated to observe the bound of approximation error real-time.
The approximation error level is influenced by the amplitude of disturbances.
The approximation error is defined in the worst case, average case and randomized settings.
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CEO of Professional Science Editing for Scientists @ prosciediting.com