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The interest in deriving mean field equations from stochastic microscopic model has been revived recently as it contains the possibility to derive deterministic 'corrections' to the mean field equations, also called second-order approximations.
These tools do not resolve turbulent fluctuations responsible for the bulk of cross-field transport in the Scrape-off Layer (SOL), and solve mean field equations instead.
The region of retrieval obtained from the mean field equations was validated with computer simulations of the corresponding networks of binary neurons (white discs, 95%% success rate).
Failures owing to activity explosion (the lower side of the wedge) are almost independent of the skewness, due to the instantaneous feedback inhibition in the mean field equations.
We derive the averaged mean field equations and show that there are changes in the stability as the homeostatic time constant changes.
As is thoroughly discussed in [5] establishing the connection between master equation models and mean field equations involves two limit procedures.
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Assume that X and Y are two solutions of the mean-field equations (Equation 22).
In the section above, some theoretical results for the proposed mean-field equations are revealed.
This leads to significant differences in the corrections to the mean-field equations.
We have proved the well-posedness of the mean-field equations.
The price to pay is the complexity of the resulting mean-field equations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com