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Furthermore, we discuss the robustness of DMD- and POD-based reduced-order models with respect to variations in initial conditions, permeability fields, and forcing terms.
In this section, we discuss the robustness of the set-membership NLMS (SM-NLMS) algorithm.
In this subsection, simulations are conducted to discuss the robustness of the controller.
We discuss the robustness of these results to learning, and to other forms of prioritarian social welfare functions.
At last, we discuss the robustness of our method and the effectiveness of the termination criterion in the experiment.
So it is essential to discuss the robustness of the high-order superdirectivity before our methods are presented.
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Shen and Wang [15] discussed the robustness of global exponential stability of nonlinear systems in the presence of time delays and neutral terms.
We have not discussed the robustness of attraction properties of RHCs - mere existence of a RHC is not enough to guarantee that it will be an attractor, but we mention that as attraction properties are determined by open conditions on eigenvalues of the saddles (e.g. [1, 24, 35]), continuity of variation of the eigenvalues will guarantee that attractivity is also a robust property.
We discussed the robustness of oscillatory dynamics to changes in the shape and size of the cell and nucleus for our core oscillator model in section 2.2.1.
We also discussed the robustness of our results with respect to different choices of parameters and feedback function forms.
It may be timely for those involved in the construction of questionnaires to consider some of the dimensions used by epidemiologists when discussing the robustness of a new testing procedure.
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