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This problem can be modeled as ∥f⊗H−B∥, where ⊗ is a convolution operator.
This problem can be modeled as a so-called high-cost nonlinear programming problem.
This problem can be modeled as a combinatorial optimization problem, in which a given set of rectangles in floorplan must be arranged.
This problem can be modeled as a search for the path with minimum cost in a graph, and the A-Star algorithm has been adapted to solve it sequentially and in parallel.
This problem can be modeled as follows: y = A x ∗ (1).
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For this situation, the problem can be modeled as uncapacitated FLP UFLPP) which this study was addressed to.
Therefore, the problem can be modeled as a simulation optimization problem, where the objective function cannot be evaluated exactly.
We show that the problem can be modeled as a special case of the single-depot vehicle scheduling problem, which is polynomially solvable.
With the a priori information that Doppler signatures corresponding to different bistatic links share the same set of motion parameters, the problem can be modeled as a group sparse signal reconstruction problem.
In this paper, we show how the problem can be modelled as a minimum cost flow problem with side constraints.
Whenever the compatibility of the objects can be checked by a pair-wise comparison the problem can be modelled using the graph theoretic notion of cliques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com