Sentence examples for variability estimation from inspiring English sources
(E ) An estimator where both P and q change yielded the lowest variability estimation error, compared to estimators where P or q were fixed.
An efficient gate delay variability estimation method is proposed for variability-aware design.
Variability estimation of NWFET is essential to design the next generation logic circuits.
Additional file 1: Detailed descriptions of the radiolabelling procedure, image analysis, γ-counting procedure and analysis, and intersubject variability estimation.
The hypothesis of this study is that pulse arrival time and changes in photoplethysmogram signal waveform (instantaneous photoplethysmogram signal frequencies) could be used as the surrogate parameters for blood pressure variability estimation.
Finally, with the decision and optimization process, an achievement function approach was applied to solve MOO modification for the Pareto front, and the sensitivity-based variability estimation is used to identify the robust solution.
Using these (individual+technical) variability estimations we calculated the number of expected genes according to an EV occurrence.
To determine if differences in coverage among the studied strains affected the reliability of the variability estimations, we took readings representing ~1× sequence coverages of seven E. coli genomes and complete-genome readings (about 10×) of the same genomes from GenBank (ftp://ftp.ncbi.nih.gov/genomes/) and assembled these readings using the Celera assembler [ 53].
In language total variability space estimation, total variability space is estimated relative to UBM, which is language, speaker, channel, gender, and environment independent.
Then, the process of language total variability space estimation is exactly the same as the process of total variability space estimation and eigenvoice space estimation in speaker recognition.
To deal with the inter- and intra-patient variability, an estimation strategy, the multiparametric moving horizon estimator, and different robust algorithms such as Offset Correction, State-Output Correction and Prediction Output Correction are further designed and implemented simultaneously with the hybrid multiparametric model predictive control.
