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Both the computing time and storage required by FCM are significantly reduced; the computation speed can reach about 18 mega points per minute on the personal computer.
Since the tensor-product convolution in 3D is performed via 1D convolution transforms, our scheme markedly outperforms the 3D-FFT in both the computing time and storage requirements.
As shown in Table 4, with the increase of the power system size, both the computing time and memory usage increase nonlinearly for the two schemes, and the increase for NoEDC is far more than that for EDC.
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This places a limit on the size of groups amenable to CCH analysis due both to the computing time required for such a large number of analyses, and also the reduction in statistical power due to multiple independent tests being performed.
It can be found that, when 30 is selected as the bundling distance parameter, both of the errors and the computing time are moderate, which means that a reasonable bundling distance parameter can balance accuracy and computation time.
The computing time for the conventional computer increased exponentially with the number of qubits.
However, the computing time is relatively important.
Also, it greatly increases the computing time.
bound the computing time induced by the uncertainties.
In this way, the computing time is reduced significantly as presented in Table S7.
The computing time is calculated.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com