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In this subsection, we discuss the optimization constraints.
The stability condition for our case is derived and used in the optimization constraints.
where β k is Lagrangian multiplier to satisfy the optimization constraints.
As shown in (5) and (15), the optimization constraints have the form of non-convex functions.
The lower layer optimization constraints are linear given the fixed upper layer decision variable ( varvec{x} ).
In order to make the model-based approach more efficient, we propose new global optimization constraints with dedicated filtering algorithms.
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The symbol sets were found using a random symbol search with defined in (3) being the optimizing criterion and (4) being the optimization constraint.
Optimization constraint is maximal of the momentum produced by momentum wheels.
Total variational (TV) is a very important optimization constraint in CT reconstruction and was widely studied and applied.
A decision function is defined as the boundary between two regions of a design space (e.g., an optimization constraint or a limit-state function in reliability).
Then, two specific versions of the generalized CSP are proposed, where a specific target function and optimization constraint are used for estimating the spatial and spectral filters.
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