In this paper, we evaluate the complexity of MOSKitt4ME.
In this study, to evaluate the complexity of the trust model, time complexity is considered as the main factor.
Instead of simply using single time scale to estimate the complex pattern (irregularity) of a time series, MSE extended this concept to evaluate the complexity of physiological signals on multiple time scales.
In view of the above discussion, the contributions of this paper are summarized as follows: We evaluate the complexity and memory requirements of each variance estimator.
Based on [47], one can evaluate the complexity of such an operation as 42α + 22α3 complex operations.
This means that a systematic approach that can properly evaluate the complexity of procedures is indispensable for minimizing the side effects of complicated procedures.
The findings of this research help us to advance our understanding of how to evaluate the complexity level of real-world applications by using pupillary responses.
To experimentally evaluate the complexity we performed execution-time experiments.
We evaluate the complexity by the number of scalar multiplications and square roots.
We evaluate the complexity and memory requirements of each variance estimator.
