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Sensitivity analysis proved robustness of the results.
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Moreover, we prove robustness of recovery under perturbation of the measurements by noise.
Moreover, noise was introduced at different SNR values in the measured signal, and performance was evaluated to prove robustness of the proposed system against the background noise.
In Section 2 we give a converse Lyapunov theorem mentioned above, and in Section 3 we prove robustness of exponential dissipativity.
We give a converse Lyapunov theorem and prove robustness of uniform exponential dissipativity with respect to unbounded external perturbations, without assuming being globally Lipschitz in.
Different communication channel models are used in the validation stage to further prove robustness of the proposed methodology with respect hard delay and packets losses.
While results prove robustness of the compromise effect even in the binding choice context, its magnitude is significantly reduced, hence indicating a hypothetical bias.
For the special case of linear systems, and under only time-varying delay perturbations, we prove robustness of global exponential stability of the predictor feedback when the delay perturbation and its rate are small in any one of four different metrics.
This proves robustness of the procedure.
In general, we recommend the investigation of biomarker profile after transplantation to prove robustness and reliability of these biomarkers.
In most implementations of WGP, the GBLUP approach is recommended as a benchmarking method because of its proven robustness.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com