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The process consists of three processes, which are node registry, neighbor selection, and update criterion [11].
An iterative algorithm using (28) as the power update criterion using γ k [n], p k [ 0 ] = p ̲ for all STs k, without the exit condition on the GLRT converges to p Δ ⋆, as confirmed by Corollary 1.
The reason for this action will become clearer later on in the proof of Theorem 5. Concerning penalty parameters ε t, in the centralized fashion of [17] the update criterion on ε t is of the form boldsymbol{epsilon}_{t+1} =left{ begin{array}{ll} boldsymbol{epsilon}_{t} & text{if}, Gamma_{t+1}letheta,Gamma_{t} tau boldsymbol{epsilon}_{t} & text{otherwise} end{array} right.
It is possible that all candidate biasing parameter sets fail to satisfy the update criterion.
Possible reasons for the failure include poor choice of ρ, insufficient N, and nonexistence of candidate intermediate reaction rates that satisfy the update criterion.
In order to update the intermediate reaction rates for the next stage, we evaluate how each candidate biasing parameter set γ (l,·) performs with respect to the update criterion.
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Considering PDF update criteria in Eq. (16), if we assume τ=1, the update process will not be affected by the previous generation, i.e., p_{g+1}(mathcal{G}) = frac{tau}{J}sum_{j=1}^{J}mathcal{G}_{j:M}^{g} (17).
The value M c to update criteria and groups, and the value M mc to update meta-criteria are calculated as follows: begin{aligned} M_{c} &= log(S^{best}_{A_{R}}) M_{mc} &= frac{log(S^{best}_{A_{R}})}{n_{c} times n_{l}} end{aligned} (3).
With each new Panda update, criteria for which content is analyzed becomes much more sophisticated.
The laboratory criteria of update criteria for definite antiphospholipid syndrome (APS) includes the lupus anticoagulant (LAC), the anticardiolipin antibody (aCL), and the anti-β2 glycoprotein I (β2GPI) antibody [ 13].
At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com