Sentence examples for model with offset from inspiring English sources

First, a novel MIMO received data model with offset symbol is proposed to prevent the CFO from causing symbol detection failure in the STBC MC-CDMA system.

The first stage of the receiver uses a novel MIMO receiver model with offset symbols to achieve a fuzzy CFO-constrained MOE detector that suppresses multiple access interference (MAI) and minimizes cancellation of the desired signal.

A curve-fit random error estimate method was employed for a proportional model with offset.

A Poisson regression model with offset [ 30] was used to assess the evolution of the percentage of SDM publications with respect to the overall number of publications in a year.

The random effects meta-analysis to obtain the overall failure rate ratio of a number of comparative studies was based on the random intercept logistic regression model with offset variable, as described by Stijnen et al. [ 12].

The model with the offset has a lower global deviance then the model without the offset but the difference is not large.

Since the polynomial model with the offset does not lead to a better model, and the polynomial model without the offset is the same as the bent-cable model, pursuing the latter seems the best choice.

The Arraystat normalization parameters used were "proportional model with offsets, no outlier exclusion," which log transforms the data (log10) and globally centers the transformed data within conditions by subtracting the array mean for all genes present on all arrays in the condition and adding the condition mean for all arrays in the condition.

In comparison of the performances of the full-spectra (680 950 nm) PLS regression model and the feature wavelengths PLS regression model showed that the MC-UVE GA PLS MC-UVE GA PLSseline offset correction comodeld multiplicative scatter correction (MSC) pretreatment withmuch baselinend 14 variables in toffsetere selecorrection

The initial Poisson model (with the offset variable only) provided a deviance equal to 161.20, which was much greater than the degrees of freedom (equal to 40), suggesting a strong heterogeneity.

To find realistic representations of the S t, j, we fitted Model [6], using each specification of confounders(α = 1.2) t to the actual Seattle data using a Poisson log-linear generalized linear model with an offset term allowing the effect of PM2.5 to be set equal to θ.