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This paper presents several localized power-aware 3D position-based routing algorithms that increase the lifetime of a network by maximizing the average lifetime of its nodes.
These automatically chosen parameters were learned by maximizing the average Dice's coefficient (as explained in the following section) across the training images over a set of potential parameter combinations.
Secondly, with the partial CSIT knowledge we derive suboptimal precoders by maximizing the average MI.
It provided a new criterion for determining the optimal rotation angle by maximizing the average mutual information (AMI).
Furthermore, we have derived the optimum power allocation between two cooperative transmission phases by maximizing the average received SNR at the destination.
The method is based on a hierarchical optimization of the bit node irregularity profile for each sensitivity class within the codeword by maximizing the average bit node degree while guaranteeing a minimum degree as high as possible.
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The number of clusters was determined by maximizing the overall average silhouette width (ASW).
Third, the resource allocation determined by the previous algorithms can be inefficient in maximizing the average PSNR.
Two new objectives are considered: maximizing the average available cash, maximizing the minimum available cash.
At each step, the joined clusters are those maximizing the average gain.
For uniform weights, this is equivalent to maximizing the average pairwise similarity.
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CEO of Professional Science Editing for Scientists @ prosciediting.com