Sliding modes are used to determine best values for parameters in neural network learning rules, thereby robustness in learning control can be improved.
Sensitivity analysis was undertaken to assess the robustness of the model estimates to changes in key variables.
What do the state and control variables look like and how can the robustness parameter affect the state variables and the objective function?
However, the difficulties in a theoretical explanation of robustness within the linguistic modelling suggested the adoption of an empirical notion.
By examining children who come to the task of language development facing environmental risks, the robustness of these sequences becomes evident.
The aim of this work is to obtain an algorithm for camera pose recovery offering improved performance (in terms of efficiency, robustness and accuracy).
The effectiveness and robustness characteristics of our proposed method were verified successfully in both simulations and experiments.
I examine the robustness of monetary equilibria in a random-matching model, where a more efficient mechanism for trade is available.
