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This is because the regularized method and the iterative means are used in the third stage, which preserves the edges while suppressing the noise and removing the haze.
In the proposed algorithm, since the regularized method and iterative means are used in the third stage, this preserves the edges and reduces the pseudo-edge effects (see the detailed regions in Figure 10).
Figure 2 shows that the total computing time to calculate all the relevant modes of G 0, 0 (E) for E ∈ [-1,1] eV with spacing of 0.001 eV via analytical, i.e., (17), and iterative means, i.e., (6 - 13) for a range of GNR width on a typical duo core PC using MATLAB.
The pairwise approach proposed by Yang et al. [59] is an efficient iterative means for computing synonymous and nonsynonymous substitution rates.
Iterative means that the process is reproduced again and again on a daily basis.
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For image restoration, an Adaptive Iterative Mean (AIM) filter is presented.
Noisy pixels are detected based on iterative measuring the image entropy and restored using an Adaptive Iterative Mean filter (AIM).
In the first stage, we apply an iterative impulse detector, exploiting the image entropy, to identify the corrupted pixels and then employ an Adaptive Iterative Mean filter to restore them.
The algorithm employs iterative mean squared error minimization using least squares curve fitting [64].
Expanding this approach, Liu and Müller proposed a non-parametric time-synchronized iterative mean updating technique to construct modes of temporal structure in gene expression profiles [ 12].
The approach builds on previous recommendations for Direct DBD and gives the designer a simplified non-iterative means of controlling the system damping of the structures by choosing proportions of force resisted by the dampers relative to the main structure.
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CEO of Professional Science Editing for Scientists @ prosciediting.com