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This new approach is compared with an existing one based on an optimization algorithm and Monte Carlo simulations.
The experiments shown as examples are those in which the computer executes a catalytic reaction, changing one or more experimental variables(T, F, Pj) =X based on an optimization strategy and the data obtained until an optimum reaction condition(Xo p t) that maximizes the yield(Y) of an object product and the maximum yield(Ym a x) are obtained.
An UE grouping strategy is developed based on an optimization technique to determine which pico UEs use either the normal subframes or the protected subframes.
The proposed EMS is based on an optimization algorithm.
To address this issue, we propose a regularized deconvolution method (RDM) based on an optimization procedure.
The method is based on an optimization process that minimizes a proposed merit function.
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The bin and the window size were selected basing on an optimization process.
Our centralized baseline algorithm is based on an alternating optimization approach, solving scheduling and power optimization in the virtual control plane separately.
The authors propose two methods, based on an LP optimization formulation, for finding the optimal scaling factors μ m.
The optimization is then performed using the algorithm EM (Expectation-Maximization) based on an iterative optimization of the model parameters (a priori probability, vectors means, and covariances matrices).
The proposed algorithm is based on an alternating optimization scheme, which is intrinsically non-convex, and hence, its initialization plays an important role.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com