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The proposed adaptive digital predistorter has much higher convergence rate as compared to other LUT-based adaptive digital predistorters.
In this study, a low complexity adaptive digital predistorter with much higher convergence rate as compared to other LUT-based adaptive digital predistorters has been presented.
In comparison, the gradient-based local optimizations have a much higher convergence speed, but the solution quality depends heavily on starting points [ 14, 19].
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Computer simulations show that the proposed GA exhibits much faster computation speed so as to satisfy the real-time requirement, and much higher rate of convergence than other algorithms.
As shown in Figure 3, although there are few overlaps at the individual miRNA level, there is a much higher degree of convergence at the pathway level regulated by identified miRNAs.
This additional mechanism leads to a noticeable improvement of convergence times (Fig. 6c) and a much higher percentage of convergent cases (Fig. 6d).
Some authors suggested a much higher prevalence of ocular convergence defects in TMD adults presenting with a limited maximal opening, myofascial pain and pain in the neck and shoulder area [ 18].
However, from numerical experiments, the numerical convergence order is much higher than 1.
The effect is dramatic: after convergence the profiles have a much higher log-likelihood than they do without the misalignment correction.
While this requires much higher computational cost and is also more likely to encounter convergence problems, it does ensure high accuracy in the analysis.
The vertical scale of fluctuation has a much higher effect on the probabilistic result with respect to the tunnel convergence than the horizontal scale of fluctuation.
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