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(Convex regularization of a nonconvex function).
In this paper, we consider to minimize the sum of a nonconvex function and a convex function with the form of (1).
On one hand, we generalize the method of [9] from minimizing the sum of two convex functions to the sum of a nonconvex function and a convex function.
In this paper, we propose an alternating linearization bundle method for minimizing the sum of a nonconvex function and a convex function, both of which are not necessarily differentiable.
The first set of seven problems are generalized from the unconstrained versions in [25] by imposing suitable constraints, the second set of two nonconvex unconstrained problems are taken from [13, 26] which are the sum of a nonconvex function and a convex function.
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Given the channel conditions, the capacity of successful transmission link between a pair of SUs is a nonconvex function of transmit power vector P.
The objective function of problem (4) is also the sum of a convex function and a nonconvex function.
It should be noted that the criterion defined in (13) is a nonconvex function of, and it is difficult to obtain its global optimal solution.
It should be noted that the criterion in Equation 23 is a nonconvex function of x i, j ( t ), and it is difficult to obtain the global optimal solution.
Specifically, Equation 34 is a nonconvex function of y and a, but the first term in Equation 34 is a function only of 1 wh 1 ′ y = ρ and μ D ̂ ′ a = ω and, thus, we rewrite Equation 33 in the same way as that in the previous subsection.
In terms of optimization, nonconvex problems appeared in CS can be divided into three classes: minimizing a nonconvex function on a convex set; minimizing a convex/nonconvex function on a nonconvex set; minimizing a convex/nonconvex function on a convex/nonconvex set with integer variables.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com