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We can also observe that the capacity values for the RPDA do not change much with this new normalization, unlike the RCPA values, whose mean sum capacity values are significantly improved by forcing both modes to receive the same power.
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Furthermore, three other proposed design examples achieve better bit error rate, mean square error, and sum capacity performances than the proposed IA-equivalent SVD example design, respectively.
Furthermore, it is shown numerically that three other proposed examples achieve better bit error rate, mean square error, and sum capacity performances than the proposed IA-equivalent SVD example, respectively.
In [10], at high signal-to-interference noise ratio (SINR), a feedback allocation strategy has been presented to reduce mean loss caused by the random vector quantizer (RVQ) in sum capacity.
Indeed, it is quite conceivable that the appropriate games for these scenarios are not convex or concave, and it is even conceivable that such games may not be balanced, which may mean that there are unexpected limitations to achieving the sum rate or sum capacity that one may hope for at first sight.
With higher Δ values, the sum capacity target is exceeded and the used sum power slightly increases, which means that the accuracy of the algorithm (in terms of keeping the sum rate target) somewhat decreases (middle).
Mean sum of squares.
The HAMA mean sum score at screening was 20.5 ± 5.4.
zero mean sum of absolute differences.
Models were mixed using mean (sum) rule, weighted mean, and stacked generalization ensemble methods.
Using the SINR and (6), we calculate sum capacity.
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Justyna Jupowicz-Kozak
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