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The setting of the optimization problem is in the most general form, which makes this work a nontrivial extension of [1].
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Next, the feasible set of the optimization problem is reduced.
We note that the value of ϕ j depends on the set of the optimization vectors.
This process guarantees that the chosen paths are in the set of the optimization paths.
The first set of the optimization parameters are related to parameter regularization which is used for typical MAP adaptation.
We can see that the feasible set of the optimization problem (38) is closed and bounded as in [34], p. 30, Sec.
For all three bandlimited white noise processes and for all sets of windows, the optimization converged to the same minimum error for all the 100 cases, based on equal sets of weighting factors.
Benefits of the chosen formulation for industrial application are the ease of setting up the optimization model for arbitrary printer configurations, and the short computation times.
Then, we will demonstrate the constraint functions are all convex, guaranteeing that the feasible set of this optimization problem is convex.
We symbolize Γ for the solution set of the split optimization problem.
To reduce the complexity of the whole problem, we separate scheduling from routing and power control, including it instead in the constraint set of the joint optimization problem.
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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