Exact(2)
As stated in [27, 28], this Gaussian random model for steering vector is general because it can address the uncertainties due to many reasons, including DOA pointing error, array calibration error, scattering around the source, propagation through an inhomogeneous medium, and other systematic problems.
All validation errors after partial training are saved and compose a validation error array.
Similar(58)
We find that channel estimation error causes array gain loss while CSI delay causes diversity gain loss.
In practice, many factors can lead to steering vector estimation errors, such as inaccurate signal model [4], direction of arrival (DOA) estimation error [5], array perturbations [6], and calibration errors [7].
An adaptive minimum mean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading.
Furthermore, one can find that channel estimation error causes array gain loss by comparing the curves of the same mobile velocity but with different pilot SNR while CSI delay causes diversity gain loss by comparing the curves of the same pilot SNR but with different mobile velocities.
GraphPad was also used to calculate p-values and standard error for Array Format 2 data.
Unfortunately confounding technical variation and systematic error in array technologies presents a major obstacle to their adoption for clinical diagnostics in humans.
Hence, under the assumption of no systematic error after array normalization, usage of σ wtrep as reliable (lower) estimate of σ total is justified.
The average normalized ratio, p-value, and standard error in Array Formats 1 and 2 of 19 transcription factors is shown, at the stage of dry seed vs. 100-200 mg cotyledons.
PLM computes standard errors of all expression measures, and these are standardized, gene by gene, across arrays, so that the median standard error across arrays is 1.
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