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Then, we design a scenario to validate the ability of the presented SW ℓ2,1-SVD, which there are two uncorrelated moving sources in the array's viewing field and we need estimate their DOAs using a few snapshots.b We consider two moving sources in this simulation.
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To use feedback in channel estimation or MIMO detection, we need estimates of the unknown data and a measure of the uncertainty left in these estimates.
We need estimates of the numbers who will come here.
For tightness, however, we need estimates for their integrals over complements of balls, as the proof of Lemma 31 reveals.
Now, we need estimates for (a) the linear term ∥ a ⏜ l + 1 − a ⏜ ∞ ∥ and (b) the quadratic term ∥ a ⏜ l + 1 ∘ a ⏜ l + 1 ¯ − a ⏜ ∞ ∘ a ⏜ ∞ ¯ ∥.
Now we need estimates which allow us to extend the solutions to the whole interval ([0, T]) and pass to limit as (mrightarrowinfty) and (epsilonrightarrow0). Hence, uniform estimates with respect to m and ϵ are needed.
We need estimated start-up expenses as shown below.
which we denote as θ, we need estimates of the DLT rate at each dose.
To obtain detection rates for the UK National Breast Screening Programme, we need estimates of the underlying incidence.
We need estimates of the prevalence of V. cholerae infection in endemic populations.
For this, we need estimates of the split time and the post-split long-term effective population size.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com