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Focusing on this issues, we proposed a particle swarm optimization-based algorithm to efficiently find optimal uniform designs with respect to the CCD criterion.
We initialize the algorithm with the optimal uniform energy and bit allocation from Section 4.1.
However, how CCD-based optimal uniform designs can be efficiently computed remains a challenge.
Many conditions to guarantee optimal uniform L 3 / 2 - L 3 estimates have been known so far.
There exists an optimal uniform Delaunay discretization with matching anisotropy with respect to the effective masses of the host material.
In Figures 11 and 12, the MDFT Neyman-Pearson detector performance is depicted, since the optimal uniform DFT detector performs similarly.
Following this idea, in [47] authors propose a new PVM scheme based on Chebyshev polynomials, which provide optimal uniform approximations to (vert xvert).
In this work, a second law analysis is applied to the optimal uniform heat generating areas with different complexity levels of the tree network of conducting paths.
The optimal uniform convergence rate of the estimator in a ball of Besov Space Bsp, q is proved under general assumptions.
For the uniform convergence rate of normalized maxima from the GED ( v ), Hall [5] established the optimal uniform convergence rate as v = 2, i.e., the normal case; Peng et al. [6] extended the result to the case of v > 1.
In the case of perfect CSI, the optimal uniform energy allocation is given by E=minleft(min_{qinmathcal{Q}}frac{mathcal{I}_{q}}{sum_{lin{mathcal{N}}}|G_{l}^{ q)}|^{2}},frac{E_{text{max}}}{|{mathcal{N}}|}right).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com