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We expected different thresholds to yield different behaviours with respect to energy efficiency, which would allow us to pick thresholds with a balanced behaviour, i.e. which would save a significant amount of energy without sacrificing too much computational performance.
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Consequently, they exhibit much better computational performance.
It is expected that RZA-NLMF using learning reweighted factor can achieve much better recovery performance without sacrificing much computational complexity.
On the other hand, the class-specific weights can be used to improve the combinative performance without increasing much computational load.
Such structures have been manufactured in practice above submicron scale so that the atomistic simulations are not tractable to evaluate their performance because the repeated computation of micro/submicro-scale in atomistic simulations requires too much computational time and resources.
Though the best performance is achieved by the SRC, it needs much computational time.
Though the maximum-likelihood (ML) detector employed at the MS or at the BS offers optimum performance by mitigating the CCI, MUI, and MSI, it often imposes too much computational complexity.
Detailed micro-modelling requires much computational effort.
Further, its computational performance is assessed too.
(21)–(22) into an MILP formulation with a better computational performance.
The second drawback is instead related to computational performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com