Your English writing platform
Discover LudwigExact(14)
We consider the egalitarian social cost, which is the maximum individual cost (instead of the sum), when analyzing Nash equilibria in fair network cost-sharing games.
Shape-preserving piecewise cubic interpolation, instead of the sum of two ICAs multiplied by the intracranial width, barely improved the Pearson correlation with the fully delineated ICV.
(5) Sometimes it is more convenient to represent Y as a product (Y_{1}timescdots times Y_{p}) instead of the sum (Y_{1}opluscdotsoplus Y_{p}).
Obeying this principle facilitates minimization of a parameter identification cost function which is the sum of long-range (multi-step) prediction error squares instead of the sum of single-step prediction error squares.
Not only that, with handover we are only able to use the capacity of just one neighbour cell, instead of the sum of the available capacity in all the neighbouring cells.
Besides, in order to satisfy the SE requirement for both uplink and downlink instead of the sum SE, we replace the required sum SE in (69) with the required uplink and downlink SE which are set to be equal (the practical case in the Fig. 5).
Similar(46)
Hence, instead of the sum-power constraint, this leads to power constraints imposed on a per-antenna basis.
Instead of minimizing the sum of squared residuals, ridge regression minimizes the penalized sum of squares | y − Xm| + λ m′ m, where λ is the penalty parameter, and the estimate of the regression coefficient is given by: m ^ = (X ′ X + λ I ) - 1 X ′ y, where I is a p × p identity matrix.
In [6] Pečarić showed that instead of variables the sum of which is equal to 2a, we can use variables the difference of which is constant, and that result becomes a source of some further generalizations [[2], pp.74, 75].
Therefore, instead of considering the sum of two independent random variables applied to the filter bank, it is equivalent to assume a single random variable that follows the distribution N ( 0, σ w 2 Σ y - 2 + ( χ - 1 ) I ).
Instead of maximizing the sum of throughputs, i.e., ∑ r u, which often leads to very low throughput for some users, we minimize the sum of the inverse of throughput, i.e., ∑ r u − 1, which can be seen as the total delay spent to send an information unit to all the users.
Write better and faster with AI suggestions while staying true to your unique style.
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