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To eliminate the phase ambiguity and reduce the estimation error for small, a complementary sine estimator is generally needed.
In binary symmetrical channels (BSCs), the power scheduling is proposed to reduce the estimation MSE when the best linear unbiased estimator (BLUE) and a quasi-BLUE, where quantization noise is taken into account, are used at the FC [14].
In each case, it is demonstrated that the enhanced model can reduce the estimation error nearly by half compared to an estimator ignoring the hysteresis effect.
If the intervals are too long, the estimated results will deviate from the real values a lot and reduce the estimation accuracy.
In order to accomplish both accurate TOA estimation and to reduce the estimation time, a two-step algorithm is proposed where first a coarse TOA estimate is obtained starting from received signal energy samples, then the arrival time of the first signal path is refined by considering a hypothesis testing approach.
Then, estimation results are averaged to reduce the estimation noise.
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However, the blending considerably reduced the estimation variance indicating that uncertainty of the map estimates was a neglected property necessary to detect change and difference in patterns.
A higher smoothing delay means that more measurements are available, which significantly reduces the estimation error.
Some studies in the past have suggested increasing gauge network density for reducing the estimation error.
They were then eliminated from the objective function reducing the estimation error of the identified material properties.
The augmented model is then used to design an observer which reduces the estimation bias compared to a default observer.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com