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However, this is optimized as shown in the next section.
If there is no feedback (no coefficients in Eq. 5.1)), then the difference equation and the convolution formula are essentially identical, as shown in the next section.
The sample's profile is shown in the next section.
The basic idea of DHF is shown in the next section.
Similar analysis was done for data branch and will be shown in the next section.
Tests were done and results were shown in the next section.
The proof of Theorem 1.2 will be shown in the next section.
The parameter β can be chosen according to simulations which are shown in the next section.
It is shown in the next section that approximated probabilities are close to the simulation results.
On the contrary, our implementation needs much improvement, which is shown in the next section.
Vertical displacement is superior to horizontal displacement, as shown in the next section.
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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