Sentence examples for large robustness from inspiring English sources

It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as the consistent estimation of parameters including large robustness to parameter variations and external disturbances.

It initially uses two quality models (the quality model of translational constraint and the quality model of rotational constraint) to combinatorically represent the quality of caging and finds the optimized finger positions (finger positions that have large robustness to perception noises) by maximizing the margins to caging breaking.

The optimization approach proposed in this paper provides the large and uniform domains of attraction of the prototype patterns, the large robustness margin for the weight matrix of the perturbed BSB neural network, the asymptotic stability of the prototype patterns, and the global stability of the BSB neural network.

Contrary to the findings in [8], [10], [11], we conclude that the LL model has a large robustness region with a quite irregular shape.

The positive slope of the robustness curve in Figure 1 expresses the trade off between robustness and performance: large robustness entails large prevalence at the specified target time (10 years).

The main results for regional robustness are in agreement with the habitat heterogeneity hypothesis, as the largest robustness is found in heterogeneous systems with intermediate dispersal rates.

By analyzing the results, the IS-MRC design that has the largest robustness to the plant uncertainties is demonstrated to provide the best overall performance.

The main interest is that continuity of the displacement field is introduced, which offers larger robustness and a greater number of measurement points for the same uncertainty level [16].

When we apply the new method to the high dimensional Laub-Loomis model, we obtain a much larger robustness region than reported earlier in the literature.

It is not clear what this comparatively larger robustness against noise in estimates of ψ can be attributed to.

Experimentally, and from the observation of Figures 1 and 3, the latter choice seems a relevant approximation of the data model from Example 1 in Section 2. The parameter λ should make a compromise between a good fit to the data (λ large) and robustness of the method (λ small).