Sentence examples for both algorithms were compared from inspiring English sources

The both algorithms were compared to show the effects of the speed changes on the ability for the both systems to correctly identify the distorted samples.

Height estimates resulted from processing lidar data with both algorithms were compared to field measurements obtained with a plot design following the USDA Forest Service Forest Inventory and Analysis (FIA) field data layout.

Both algorithms are compared in terms of sum-rate performance as well as complexity.

Both algorithms are compared using these three step sizes, and Fig. 4 summarizes the results obtained.

The results for both algorithms are compared and the relative mean error in axial direction is 0.30% and 0.48%.

Performances of both algorithms are compared to that of the ML algorithm in order to evaluate the performance loss of each protection class provided by less complex algorithms.

The performances of both algorithms are compared to that of the maximum likelihood algorithm in order to evaluate the performance loss of each protection class provided by less complex algorithms as well as their complexities are evaluated according to the number of arithmetic operations performed at each decoding step.

Next, the values of γ under both simulation algorithms were compared under conditions of incomplete taxon sampling (ranging from 95% to 20% taxon sampling).

All six algorithms were compared both on the training set and on the testing set with optimal feature subsets of their own.

The two algorithms were compared in terms of both performance and complexity.

Popular optimization algorithms were compared and discussed.