Your English writing platform
Discover LudwigExact(13)
(A) Curves of correlation outputs.
Figure 4 Correlation outputs before and after sidelobe suppression.
The correlation outputs showed that there is a deviation margin of 4%.
Moreover, by focusing on the correlation outputs at the origin, OOCTF is very effective for feature vector extraction.
The proposed scheme uses low-rate correlation outputs and is able to perform accurate TOA estimation in reasonable time intervals.
Moreover, the direct computation of the N correlation outputs in (15) requires O N2) of complex multiplications.
Similar(47)
The next correlation output can be extracted directly from the estimated correlation output by setting the memory address step by 1 and repeat what is done for the evaluation of the first correlation output.
Comparison between the evaluated correlation results is done on the fly after every new correlation output.
As a result, there is an extra Multiple Access Interference (MAI) term in the correlation output.
As shown in Fig. 2b, a 1D Gaussian is implied as the desired correlation output g.
Figure 4 Correlation output of the proposed coarse timing synchronization block.
Write better and faster with AI suggestions while staying true to your unique style.
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