Sentence examples for models we compare from inspiring English sources

Coupling the shift behavior explained above with the models, we compare awareness/attention index of agents with quality of regional density information.

In order to validate the dynamic characteristics of the current models, we compare the STFs with that obtained by the kinematic slip inversion analysis.

To distinguish empirically between parallel and serial parsing models, we compare ERP responses to garden-path sentences with ERP responses to truly ungrammatical sentences.

To assess the significance and goodness-of-fit of the models, we compare the deviances through a Chi-square test (also known as the 'likelihood ratio test') (Hayes 2006).

In the experiments, through the compressed sensing and image deconvolution models, we compare the proposed stepsizes with the former ones, the results obtained from the proposed stepsizes and algorithms appear to be significantly better.

Utilizing extracted models, we compare optical NoC with electrical one and calculate lower bound limit on the optical link length below which optical on-chip network loses its efficiency.

To check these models, we compared these models MSE in both previous and recent simulation studies.

As part of the evaluation of IGRF-11 candidate models, we compared candidate models and actual measurements.

To assess these models, we compared outcomes to a simple design-based estimate commonly used in forest inventories.

To further evaluate the prediction ability of our models, we compared our prediction results with the published models in recent papers.

To investigate this point in the frame of GP models, we compared the performance of various kernels (Bessel, Laplacian, NP, and PUK) with the radial and polynomial kernels.