Sentence examples for error yielding from inspiring English sources

The expansion trades bias for variance of the error yielding a better model in terms of predictive performance.

The MVDR-N performs slightly better due to the partial noise estimation, but we clearly observe that the binary decision mask algorithms (IBDM, IBDM/CM, SBB, and SBB/CM) result in much lower MSC error, yielding a performance similar to the bilateral MVDR beamformer.

This may reduce the variability attributed to error, yielding cleaner data and larger effect sizes, as demonstrated by the study of Lynott and Connell (2009).

29 They judged and classified the theoretical severity of the medication error, yielding a score of 0 4 (0=drug error without significant harm, 1=potentially significant, 2=potentially serious, 3=potentially life threatening, 4=potentially fatal) (table 2).

Statistical contrasts at the single-subject level were computed as weighted sums of the estimated beta coefficients divided by an estimate of the standard error, yielding a t-statistic for each voxel in the image volume.

Each test run began at a highly visible stimulus increment and thresholds were tracked using a 3-down, 1-up staircase (contrast was reduced after three correct responses and increased after a single error) yielding a 79% correct threshold level.

A similar property is also established for a set of invariant stabilization errors yielding a different controller design option.

It confirms that the algorithm is able to reduce discontinuity errors, yielding a homogenized ECa surface that is continuous across field boundaries.

The obtained controller is complemented by additional conditions established for guaranteeing string stability and zero steady state velocity errors, yielding a useful string stable platoon control method.

The T2 density profile must have a stability of 10−3 in order to limit the systematic errors, yielding stringent requirements on the beam tube temperature homogeneity and stability of ±30mK.

To do so, our algorithm takes advantage of the training stage of a MSVM, making it possible to obtain the set of paths that maximize the distance to the obstacles while minimizing the effect of measurement errors, yielding paths even when the input data are not sufficiently clear.