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The design minimizes the radiation escaping from the pixels while maximizing the random diffraction.
In both figures, we observe that there is a tradeoff between the throughput and reliability and a need to compute the optimal density of transmitting nodes for the purpose of maximizing the random access transport capacity.
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Using the upper bound for multihop AF relaying, the optimal density of transmitting nodes λ o pt u pp which maximizes the random access transport capacity can be written as λ o pt u pp = arg max λ C AF u pp. (24).
We can maximize by maximizing the coefficient of the random variable in (27), and the optimal is given as follows: (37).
The first one is by maximizing the mutual information between the random target impulse response and the reflected waveforms, and the second one is by minimizing the mean square error in estimating the target impulse response.
Our decision is justified by the observation that, assuming independent random experiments, maximizing the posterior when deciding on a hypothesis in each will maximize the posterior over all choices because in this case the posterior over all choices is equal to the product of the individual choices.
We estimated parameters with random effects (one intercept by plot 1|plot) and fixed effects using maximum likelihood by maximizing the joint density of the parameters and the random component.
Design strains are finally established by maximizing the analytical expressions against the unknown, random angles of wave incidence.
A powerful experimental design should aim at maximizing the proportion of causal loci vs. random noise in the selected populations.
The diffusion of the molecule in the focal volume is random, and the optimal trajectory maximizing the numbers of photons emitted is exponentially rare.
DF attempts to minimize overfitting by maximizing the difference among individual trees to cancel some random noise through combining the trees.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com