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This approximation may be considered as a good lower bound for any MIMO system in the presence of impulsive noise.
It may be considered as a good lower bound for 2×2 MIMO systems in the presence of impulsive noise.
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Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound.
Obtaining a "good" lower bound is somewhat more involved.
Work out the upper bound and lower bound for the following measurements.
The lower bound for y is y equals x.
A lower bound for two-server balancing algorithms.
A lower bound for the first elastic eigenfrequency is obtained.
The lower bound for the total variation (TV) is established.
The other involves an approximation of the global lower bound for the branch and bound solution.
This is, as far as we know, the first constructive superlinear lower bound for R 3,t).
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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