Resource demands are a key parameter of stochastic performance models that needs to be determined when performing a quantitative performance analysis of a system.
In this section, we perform a comprehensive performance analysis of the system under consideration by presenting closed-form analytical expressions for key performance measures, i.e., the outage probability, the average SER, and the ergodic capacity.
Because of these similarities, we performed a comparative performance analysis of some capabilities offered by both packages.
A performance analysis is performed to demonstrate the benefit of DrMoM over existing region-based location management schemes.
We have performed an initial performance analysis to measure the impact of the attestation protocol on authentication.
SONLAB data structures and algorithms are designed to perform network performance analysis, such as load and SINR computations for a large amount of users and cells, within a few seconds.
In Section 4, we perform rigorous performance analysis to show energy consumption, impact of change in packet length, performance under transmission errors and decomposition of energy.
We derive some closed-form expressions for the outage probability involving SIC, and we perform a semi-analytical performance analysis in terms of outage probability and spectral efficiency.
To test whether social functioning was predicted by mental state decoding performance (Eyes task performance) we performed a multiple regression analysis with ILS scores as the dependent variable.
To demonstrate the parallel solution and gradient evaluation performance, we perform a structural analysis and gradient evaluation for a large transport aircraft wing with over 5.44 million unknowns.
In order to get an insight into the descriptor performance we performed a PCA analysis on target space again (Figure 11, Additional file 1: Figures S14, S15, S16).
