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Furthermore, the proposed robust methods significantly outperform the nonrobust method when the channel estimates are imperfect.
It can be observed from this figure that the proposed robust methods significantly outperform the nonrobust method.
Overall, the mean angular error of OMP over all 95 materials is 6.3174°, on par with SBL (6.5370°), and both methods significantly outperform the naive LS (10.8027°).
The experimental results clearly indicate that these methods significantly outperform the traditional approaches with a dramatic reduction in the computational efficiency to update the rough approximations.
We find that on the SRDS1 versions of the datasets, both the LA and the CTD methods significantly outperform the 5-spectrum kernel and that there are no statistically significant differences between the LA kernel and the CTD classifier.
Both of these methods significantly outperform bp-distance (Dataset2 AUC = 0.735, Dataset3 AUC = 0.766).
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Our study finds large differences in forecast error rates between the two groups, with users of quantitative methods significantly outperforming users of judgmental methods.
All the three methods significantly outperformed Lasso regression coefficients.
This is in sharp contrast to the evaluation results based on co-regulatory networks, where both methods significantly outperformed the naive method.
Both methods significantly outperformed the random selection with margins of 1.5 (P < 1.4 × 10 − 44 ) experiments for maximum entropy and 3.25 (P < 5.3 × 10 − 191 ) experiments for the maximum difference design.
Results presented show that the proposed method significantly outperform all baseline methods in the means of both, the PSNR and the SSIM measure.
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CEO of Professional Science Editing for Scientists @ prosciediting.com