The phrase "robustness to error" is correct and usable in written English.
It can be used in contexts discussing systems, processes, or methodologies that maintain performance despite the presence of errors.
Example: "The software's robustness to error ensures that it continues to function correctly even when unexpected inputs are encountered."
Alternatives: "error resilience" or "fault tolerance."
The Electoral College appears to fail miserably based on the robustness to error criteria.
Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks.
Therefore, a distance-based reconstruction algorithm is useful in a realistic setting only if it has some robustness to error in distance estimation.
This shows the algorithm's robustness to error, even when the overall phasing yield (in terms of % of alleles phased) is low.
The prevalence at 20 years will be no worse than 2% provided that the model coefficients err by no more than 8%, and at 30 years the robustness to error is 12%.
Long-term usage of targeted BG control requires successfully forecasting variations in neonatal metabolic state, accounting for differences in clinical practices between units, and demonstrating robustness to errors that can occur in everyday clinical usage.
While RABs seek to improve the robustness to errors in the DOAs and the signal propagation vectors, ISFs address the estimation of propagation vectors and signal statistics from the microphone signals, and their usage for optimal spatial filtering.
As a result, there are emerging and compelling changes in system requirements such as more efficient spectrum usage, higher sensitivities, greater information content, improved robustness to errors, and reduced interference emissions [4, 5].
For a complete analysis of its robustness to errors, we use short and long reads with different error rates.
The standard code appears to be the result of partial optimization of a random code for robustness to errors of translation.
Of course, the hypothesis that the code evolved to maximize robustness to errors of translation [ 14] is by no means the only plausible scenario of the code evolution.
