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In this numerical implementation, the error ∥u - u h ∥0, ∥ p- p h ∥div, ∥y - y h ∥0, ∥ q- q h ∥div, and ∥z - z h ∥0 obtained on RT0 mixed finite element approximation and RT1 mixed finite element approximation for state function are presented in Tables 1, 2, 3 and 4. The theoretical results can be observed clearly from the data.
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To further quantify any potential error introduced in the implementation, the relative error E[ i r][ i z] is computed for each voxel using Eq. (1).
Today's implementation of the error 53 is a bad one, and I hope that Apple is going to fix it in the next iOS release.
A more detailed discussion and the actual implementation of the error measurements are presented in the appendix.
The filtered-x least-mean-square (FXLMS) adaptive filter is used as a benchmark for comparison with a new implementation of the error-driven minimal controller synthesis (Er-MCSI) adaptive controller.
For digital communication applications, the most commonly used criterion for evaluating the precision of fixed-point implementation is the error-rate performance degradation.
The conventional Cauchy-Born rule, however, is not accurate enough in numerical implementations, and the errors can be removed mostly by including higher-order terms based on Taylor series.
The proposed filter is not only robust against the uncertainties in the system model and measurement model, but also non-fragile against the implementation error with the filter parameters.
Another circuit non-ideality is the implementation error of the circuit parameters.
Both of these tools are complementary and offer significant advantages, such as the guarantee of finding the optimal model and the implementation of error bars on the computed output.
The third is the implementation error.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com