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It can be used to improve robustness in an existing estimator or design a new robust estimator.
A modification to the solver is proposed to improve robustness against these model errors.
In this paper, we propose two new conditions to improve robustness at second order KKT conditions.
To improve robustness, the algorithm is applied to low frequency components of the host signal.
To improve robustness, a multi-material scale separation model is developed to remove consistently non-resolved interface scales.
We proposed a ratiometric RGB filter to improve robustness under real lighting condition with less computational burden of transformation.
An individual-specific ensemble of exemplar-SVM (e-SVM) classifiers is thereby designed to improve robustness to intra-class variations.
Experimental results show that the proposed fractional order based MIMO control system is able to improve robustness and decoupling.
The internal model control based strategy is used to improve robustness for communication delays of the secondary level.
The method is direct, general, easy to implement, and allows for the addition of derivative constraints to improve robustness.
The multimodel concept allows to improve robustness of the designed strategies in the case of presence of some parametric uncertainty.
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