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Table 7 shows the impact of different assumptions related to the efficacy inputs (distribution of patients across health states).
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Based on our proposed method, the input distribution of non-linear activation is relatively scattered.
The developed surrogate models are then utilized to forecast production for any input distribution of permeability using Monte Carlo simulations.
It is found that the input distribution of non-linear activation is like Gaussian distribution and the most of the inputs are concentrated near zero.
The welds by TPAW have smaller MZ area and smaller HAZ area but similar penetration in comparison with those by PAW, the ones by NPAW could not observe MZ or HAZ under the same parameters, indicating that the total heat input distribution of TPAW is smaller than that of PAW and much larger than that of NPAW.
In this paper, we evaluate the sensitivity of input distribution on the output performance measures.
(b) Mutual information versus the input distribution for values of SNR of dB, dB, and dB.
where the maximum is over all input distributions of the form (12).
where the maximization is over all input distributions of the form and denotes the index of the strongest user in the th subchannel in the sense that (23).
To solve the above problems, we make full use of the input distributions of non-linear activation and propose the randomly translational non-linear activation for deep CNN.
(b) Mutual information versus the input distribution for a value of SNR of dB and different levels of turbulence strength.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com