Specifically, as the problem size increases, the computational effort increases almost linearly.
However, as it is depicted in Fig. 4, the computational time increases by increasing the sample size.
1 There can be little doubt that the speed of their operation is increasing, as computational power increases (Moore 1965; Moravec 1990).
The computational complexity increases with the increase in μ.
Increasing the resolution, both of the accuracy and the computational cost increase, and vice versa.
Computational time increases along with increasing indicators in pairwise comparisons.
However, for large tasks the computational load increases rapidly for increasing task length.
However, the computational requirements increase significantly for eigenface generation and projection.
The results of the H training set suggest that SGBM computational times increase exponentially with resolution.
The simulation results show that the computational efficiency increase by 5 times.
