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Sufficient conditions for extinction, persistence in the mean, and stochastic permanence of the system are established.
Secondly, we analyze the persistence in mean and stochastic persistence of the system, respectively.
In Section 3, we obtain sufficient conditions for extinction, persistence in the mean, and stochastic permanence.
The nonstationary wind speed is characterized by deterministic time-varying mean and stochastic fluctuating components.
The wind-induced response of the conductor is decomposed into deterministic time-varying mean and stochastic dynamic components.
We establish sufficient conditions for the extinction, nonpersistence in the mean, weak persistence, persistence in the mean and stochastic permanence of the system.
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The paper by Cowan, Neuman and van Drongelen in the present collection [24] reviews the historical development of the mean field and stochastic Wilson Cowan equations, and describes new results related to the statistical behavior of cortex under resting conditions and in response to weak and strong stimulation.
This method is both extremely accurate at finding the mean and fully stochastic, that is each simulation gives a different stochastic realisation and the full probability density can be found from a histogram of many simulations.
These findings suggest stochastic effects, community structure and the heterogeneity of individuals play an irreducible and non-trivial role in the relaxation dynamics, and are thus likely to be responsible for the different outcomes between the mean-field and stochastic approaches.
We are motivated to develop a mean-field approach on two counts: first, if we can demonstrate close qualitative and quantitative behaviour between the mean-field and stochastic models, then it may be far simpler to implement predictions based on analytic calculations rather than running full simulations.
In this study, we developed mean-field and stochastic models to investigate possible causes of sequential outbreaks from a public health perspective.
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