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With the inclusion of the new variable r1i in the problem, it can be verified that problem (P1) turns out to be a convex optimization problem (as the objective function is convex over {r1i} and all the constraints specify a convex set over T i 's and {r1i} [19]).
Similar(59)
It can be verified that the problem is strictly non-convex, and thus it is difficult to find an analytical solution.
It can directly be verified that the relaxed problem is convex and has no duality gap [10].
In addition, it can be verified that the optimization problem (8a) and (8b) is convex; therefore, its optimal solution can be obtained by any standard convex optimization algorithm.
For we define where It can easily be verified that the homogeneous problem associated with (1.1 - 1.2 1.1 - 1.2 thastrivial sonlyion.
For this problem, it can be verified that K is well-positioned and F satisfies assumptions (i) and (ii) of Theorem 3.4 and F u,x,.) is not C-convex.
It is verified that the problem has the solution (x^= 1, 0, 0)) easily.
It is verified that the SDR problem (7) is jointly convex with respect to the primal variables and satisfies the Slater's condition [17].
After a detailed analysis, it was verified that most of these problems occurred due to concentration estimation of simulation points located at high altitudes, typically over 4000 km of altitude.
From the vortex convection and vortex shedding problems, it is verified that the improved CBC shows better performance in accuracy compared to the conventional CBC approaches.
It is not hard to verify that Problem (25) is still nonconvex.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com