Sentence examples for robustness interval from inspiring English sources

A method for determining the robustness interval specifically for individual parameters is considered in [ 9].

In summary, the analysis of robustness intervals has revealed that the model is overall much more robust when only the preservation of trends of parameters is required.

The stability and robustness the interval observer are investigated under uncertainty in the system dynamics, inputs, and initial conditions and under the state measurement errors.

The solutions have been optimized and it is shown that the scheme has some useful features such as monotonic convergence and robustness under interval matrix uncertainty.

The robustness of intervals to violations of the normality assumption was evaluated by generating effects and errors from uniform, mixture normal, and gamma distributions.

The calculation of certainty with which each tolerance intervals captures 99% coverage provides a measure of the robustness of the interval.

In this paper, we perform a robustness analysis against interval uncertainty in the model parameters for closed-loop anesthesia control.

The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs.

In this paper, we present a methodology for the robustness analysis of interval type-2 FLSs (IT2 FLSs) that also holds for T1 FLSs, hence, making it more general.

It has to be noted that for low-correlation scenarios our system is not able to outperform the LDPCA codes, but based on the relatively small loss at p = 0.1, we note that in case of, e.g. varying values of p, the RA BCH codes do provide robustness outside the interval for which it performs better than LDPCA.

In this contribution a robustness analysis using interval methods is applied in order to determine an optimal assignment for the desired tracking error dynamics such that the trajectories of the controlled system remain within specified tolerances around the reference trajectories for a maximum uncertainty of the unknown parameters.