sum of the absolute differences.
Sum of the absolute transformed difference.
This is 1-norm and it is simply the sum of the absolute values of x i.
It minimizes the sum of the absolute values of the coefficients, with a bound on the sum of squared errors.
For example, the sum of the absolute difference in populations between all pairs of regions can be used.
Recall that the length of a polynomial is the sum of the absolute value of the coefficients.
As opposed to OLS, which is fundamentally based on minimizing the sum of squared residuals, with quantile regressions the weighted sum of the absolute deviations is minimized.
LASSO minimises the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant.
Then the energy E ( G ) of G is defined as the sum of the absolute values of these eigenvalues as E = E ( G ) = ∑ i = 1 n | λ i |.
In this scheme, a content adaptive function was used to evaluate the normalized sum of the absolute difference (SAD) between the reconstructed frames and the predicted frames.
Finally, only the sum of the absolute values of the bidimensional Fourier transform (Section 5.1.3) is retained, for the same reason.
