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The number of samples is chosen sufficiently large so that the impact of the approximation can be neglected.
The impact of the approximation (7), introduced in the previous section, is shown in Figure 3 for a single user employing 10 RB, where it can be seen to result in negligible degradation.
Our aim here is to evaluate the impact of the approximation introduced by simulating single-molecule enzymatic reactions as a Markov process through the GSSA.
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When considering the reduced model, it is important to understand the impact of the approximations underlying the linear mapping from the full model.
However, the impact of the approximations introduced by this abstraction process is difficult to evaluate or estimate, as reported by Gillespie in [ 13] for enzymatically catalysed reactions.
The impact of this approximation will depend on the specific context in which GAST is used.
The impact of this approximation will be given in the following section.
Although the impact of this approximation cannot be analyzed theoretically, the numerical results in Figure 4 show that the mismatch between the proposed analytical approximation of the RMSE and the RMSE obtained by direct simulation of the communication system is larger in the low SNR region.
This approximation has been extensively done in the literature, in Fig. 3, we verify the impact of this approximation in term of energy inaccuracy before to push further our description.
The impact of this approximation on correlation estimates, however, should be negligible.
This might not necessarily be a realistic assumption, and we will discuss the impact of this approximation in a subsequent section of this paper.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com