Your English writing platform
Discover LudwigExact(4)
a SNR = −20 dB; b SNR = −10 B; c SNR = 3 dB; d Subspace estimation deviations.
The angle estimation deviations of the proposed robust adaptive monopulse algorithm and conventional LCMV algorithm are simulated and compared.
Fig. 9 Angle estimation deviations versus SOI direction using the conventional LCMV algorithm; a deviation in θ; b deviation in φ Fig. 10 Angle estimation deviations versus SOI direction using the proposed algorithm; the dashed lines denote the boundaries of 3 dB beamwidth; a deviation in θ; b deviation in φ.
The difference between the OTU and the higher taxonomic levels may be explained by the higher probability of richness estimation deviations due to sequencing errors and short-read length at the OTU level.
Similar(56)
Scenario 3: The angle estimation deviation versus SOI direction (θ s,φ s ) is simulated.
The angle estimation deviation of the proposed algorithm is illustrated in Fig. 10 a and 10 b.
However, most of the previous studies focus overwhelmingly on unidirectional mass diffusion from collected objects to uncollected objects, while overlooking the opposite direction, leading to the risk of similarity estimation deviation and performance degradation.
On the other side, it also can be seen from Figure 3 and Figure 4 that the large estimation deviation of the system parameters at low SNR has little effect on the BER performance.
As illustrated in Fig. 9 a, b, the angle estimation deviation of conventional LCMV algorithm is obviously larger than 0.1BW (0.3°), and it deteriorates dramatically when the SOI is deviating from the look direction.
Genotype completion, MAF estimations, deviations from fitness for Hardy Weinberg proportion (HWP), pairwise linkage disequilibrium (LD) and tag SNP selection were computed using the GLU software package.
Completion, concordance, MAF estimations, deviations from fitness for Hardy Weinberg proportion, pair-wise LD, and tag SNP selection were computed using the GLU software package (http://cgfweb.nci.nih.gov/development/tooldev.html).
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