The proposed method uses isosceles triangular-shaped quantization (TSQ) of the DCT domain [6] to correctly distribute the error rates.
Since both h d and ({hat {textbf {h}}}_{d}) are zero-mean Gaussian distributed, the error vector (textbf {e}_{d} =textbf {h}_{d} - hat {{mathbf h}}_{d}) is zero-mean Gaussian distributed.
The total relative error is the absolute value of the difference between measured and modeled concentrations divided by the measured concentration; this value distributes the error evenly among the tracers included in the model (that is, the magnitude of concentration is negated).
The estimated time-series states are corrected by uniformly distributing the accumulated errors along the time sequence so that the error at the final state is canceled out.
This study is focused on the interleaving techniques to reduce the burst error effects on the audio signals through distributing the burst errors through a set of audio samples.
The predictive uncertainty factor γt* is obtained by distributing the internal predictive error sum of squares across objects in the training set based on the distances between them, hence the acronym: Distributed PRedictive Error Sum of Squares (DPRESS).
One is that according to the relationship curves, distribute the position error to each segmented mirror alone.
This was because the method uniformly distributed the attitude errors along a single rotation axis.
Because the data were not normally distributed, the standard errors were computed using the first order residual empirical estimator, also known as the sandwich estimator.
