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Broadcasting may be a suboptimal method of conveying complex treatment information in order to support shared decision-making.
It is shown that the performance of the proposed suboptimal method approaches that of the optimal PS scheme.
To overcome this, we have introduced a suboptimal method by which optimal apodization can be calculated in any distance through a nonlinear transformation by the knowledge of the optimal one at a distance.
Based on these, a suboptimal method of resource allocation to reduce such effect of quantization error is proposed, and a dynamic quantizer is designed to meet the requirement of the consensus level, under the constraints that the total quantization rate of overall system is limited.
The above suboptimal method performs reasonably well.
Fig. 8 The suboptimal method step by step.
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Falling into the category of suboptimal methods are the minimal estimability (generalization of the classical n-product formula), ordinary regression, and node imbalance methods.
Typical applications of suboptimal methods are to provide reliable estimates for data reconciliation algorithm initialization, support the selection of components to be analyzed, and to detect faults prior mass balancing calculations.
In this paper, we use tabu search to solve this feature selection problem and compare it with classic algorithms, such as sequential methods, branch and bound method, etc., and most other suboptimal methods proposed recently, such as genetic algorithm and sequential forward (backward) floating search methods.
Many suboptimal methods were presented to overcome this difficulty.
Due to the high implementation complexity of such techniques, suboptimal methods need to be examined as well.
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