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The particle position coordinates are calculated by using a reconstruction procedure that solves a minimization problem between the measured counts and calibration data.
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"That solves a real need".
Lee et al. (2010) proposed an algorithm that solves the minimization problem in Equation (4).
The aim of each player ν, given the other players' strategies x-ν, is to choose a strategy x ν that solves the minimization problem min x ν θ ν x ν, x - ν s.t.
Let be an estimate of, then any estimate that solves the minimization problem of the form (2). or by an implicit equation (3). is called an -estimate (or maximum likelihood type estimate).
The generator is found by solving a minimization problem: the norm is chosen such that the object function is quadratic and convex, so that the minimization problem can be solved using quadratic programming techniques.
Therefore, we conclude that the purpose of the existence theorems for a best proximity point is to provide sufficient conditions to solve a minimization problem.
Thus, we can say that the aim of the best proximity point theorems is to provide sufficient conditions to solve a minimization problem.
In this paper, we present SPRIT, a novel algorithm and software implementation that solves the rooted binary d R SPR minimization problem.
A popular algorithm that solves SFP (1.1) is due to Byrne's CQ algorithm [2] which is found to be a gradient-projection method (GPM) in convex minimization.
Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences.
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