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In the second step, the performance of the module has been analyzed for four cities of India such as Srinagar, Bangalore, Jodhpur and New Delhi.
In the next step, the performance of the new structure in two cases of constant time-delay and variable time-delay are evaluated and their stability conditions are analyzed.
In the second step, the performance of the hybrid models is compared with those of their base models.
After the 11th time step, the performance is even better than which in Section 6.2, because the value of the SNR of the second target is increased.
In Figure 5, the antennas are trained using 1 to 15 outdoor and 1 to 10 indoor users and in each step; the performance of the system is analyzed using 15 users randomly placed within the target area.
Whilst noise reduction has been achieved with denoising techniques implemented as a pre- or post-processing step, the performance was proven to degrade significantly at lower signal-to-noise ratios [30].
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In order to examine the effieciency of the pretrain step, the performances of pretrained and randomly initialized conventional neural networks are compared in the same setting.
Moreover, after the 200th time steps, the performance gaps between selection schemes are clearly shown.
After applying parallelization to these steps, the performance dramatically increased to 0.01 s.
This detection step enhances the performance of the total ring removal algorithm significantly.
The selection of the evaluation techniques and tools is the first and foremost step in the performance evaluation process.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com