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The maximization problem can be modified as begin{array}{cc} underset{p_{mathrm{u}}}{max} ;quad & underline E{{_{mathrm{f}}^{A}}}(;p_{mathrm{u}}) text{s.~t.~} quad &0 < p_{mathrm{u}} le p_{0}.
Thus, a DP r-mesh designed to solve one problem can be modified to solve another problem with minimal configuration.
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Then we show how the algorithms designed for these three initial problems can be modified to solve a series of related problems.
The algorithm we will describe next, although is designed for Problem (11), can be modified to solve Problem (10) that may take another form of the regularizers.
Hence, following the similar steps as in sections 3.2 and 4, the Problem P1 can be modified according to the new constraint.
In order to recover the low-rank matrix robustly, problem (1.3) can be modified to min_{X} Vert X Vert _{p}^{p} quadtext{s.t.}quad biglVert mathrm{A} ( X ) - b bigrVert _{2} le varepsilon, (1.4) where (Vert cdot Vert _{2}) is the (ell_{2}) norm of vector and (varepsilonge Vert e Vert _{2}) is some constant.
Let (S_{i}=C_{i}times Q_{i}subseteq H=H_{1}times H_{2}), (i=1,2,ldots,t), (G=[A,-B]:Hmapsto H_{3}), (G^) be the adjoint operator of G, then the original problem (1.3) can be modified as textit{finding }w= x,y inbigcap_{i=1}^{t}S_{i} textit{ which satisfies } Gw=0.
Define (K =[A,-B] : H_{1} times H_{2} rightarrow H_{1} times H_{2}), and let (K^) be the adjoint operator of K, then the original problem (1) can be modified as mbox{Find} quad z= x,y in S quad mbox{such that} quad Kw=0.
The optimization problem for EECOM can be modified from (49) as in the following: (50).
The track association problem in (33) can be modified to handle track birth and death scenarios [2].
The decision tree depends on the real problem specifications and can be modified during the dialogue between the system and the user.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com