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Exact(3)
Using this approximation and (7), (8), and (9), we can simplify (14) as.
Using this approximation and the upper bound of the quantization error, the average signal power is approximated as follows: E log h kk [ n ] w k, eg [ n ] 2 ≈ log ρ l 2 − 2 − B N t − 1 ln ( 2 ) + ψ N t ln ( 2 ).
Using this approximation, and the definition of, we see that Therefore We now consider the integral over x.
Similar(56)
By using this approximation the autocovariance and spectral density function for a certain first order system are obtained.
One major benefit of using λ m is that using this approximation, different values of D and cens can be input which enables calculation of a range of sample sizes.
Nevertheless the similarity of the correlation coefficients of the regression between B. subtilis and E. coli allows using this approximation.
Using this approximation, Eqs.
Using this approximation, we get (29).
Using this approximation, we solve the following geometric program: (24).
Using this approximation reduces the computational cost drastically.
Nonetheless, the resulting discrete values are close to the curve obtained without using this approximation.
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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