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However, provided the detailed coordinated beamforming optimization approach, the optimal values of θ and α can be achieved via one-dimensional numerical search.
With the grey Taguchi multi-objective optimization (GTMO) approach, the optimal experimental parameters can be determined and the verification experiments carried out.
Based on this approach, the optimal learning parameters can be found by utilizing the linear matrix inequality (LMI) optimization techniques to achieve a predefined H∞ "noise" attenuation level.
He laid out a better approach: "The optimal tax system... if I were doing it on a blackboard, would have been somewhat homeostatic.
Suboptimal solutions are therefore involved to approach the optimal solution.
To make the algorithm approach the optimal solution, the temperature should change with the time.
It is concluded that the performance of the proposed algorithms approach the optimal performance.
A feature-based linear approximating architecture is adopted to approach the optimal average cost.
With such approach, the optimal conversion pathway can be determined based on different optimisation objectives.
In the proposed approach, the optimal system gains are identified using the Nelder Mead simplex algorithm.
This factor normalization is key for the ML decoder to approach the optimal cost-distortion tradeoff at low SNR values.
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