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Reduction of root-mean-square error in faceted space antennas
AIAA Journal, 1984This paper examines the potential for reducing root-mean-square surface errors in shallow faceted reflectors by replacing flat facets with laterally curved membrane facets. Exact solutions are obtained for the small lateral deflections of equilateral triangular and rectangular membranes subject to isotropic tension and parabolic edge deflections. These
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Journal of Electronic Imaging, 2016
Evaluating algorithms used to assess image and video quality requires performance measures. Traditional performance measures (e.g., Pearson’s linear correlation coefficient, Spearman’s rank-order correlation coefficient, and root mean square error) compare quality predictions of algorithms to subjective mean opinion scores (mean opinion score ...
Häkkinen Jukka +2 more
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Evaluating algorithms used to assess image and video quality requires performance measures. Traditional performance measures (e.g., Pearson’s linear correlation coefficient, Spearman’s rank-order correlation coefficient, and root mean square error) compare quality predictions of algorithms to subjective mean opinion scores (mean opinion score ...
Häkkinen Jukka +2 more
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Study of Dynamometer Cards Identification Based on Root-Mean-Square Error Algorithm
International Journal of Pattern Recognition and Artificial Intelligence, 2017The surface dynamometer cards are important working condition data of sucker-rod pumping system. It has a very important practical significance for the analysis of transmission system and the diagnosis of oil production condition of sucker-rod pumping system.
Tao Ren +3 more
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Accuracy Analysis of Anisotropic Yield Functions based on the Root-Mean Square Error
AIP Conference Proceedings, 2010This paper evaluates the accuracy of popular anisotropic yield functions based on the root‐mean square error (RMSE) of the yield stresses and the R‐values. The yield functions include Hill48, Yld89, Yld91, Yld96, Yld2000‐2d, BBC2000 and Yld2000‐18p yield criteria.
Hoon Huh +6 more
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A note on minimum mean squared error estimation of signals with unit roots
Journal of Economic Dynamics and Control, 1988Using an ARIMA parametrization, this note provides a very simple proof of how the Wiener-Kolmogorov-Whittle filter to estimate signals in time series can be extended to the nonstationary case. The proof is valid for any number and type of unit roots (not simply those implied by differencing) in both the signal and the overall model.
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