Stochastic Kolmogorov systems driven by wideband noises

George Yin and Zhexin Wen

Physica A: Statistical Mechanics and its Applications, 2019, vol. 531, issue C

Abstract: In many problems arising in statistical physics, statistical mechanics, and many related fields, one needs to deal with such nonlinear stochastic differential equations as Ginzburg–Landau equations and Lotka–Volterra equations, etc. Such equations all belong to the class of stochastic Kolmogorov systems. Because of their importance and wide range of applications, these systems have received much attention in recent years. Devoted to stochastic Kolmogorov systems, in contrast to the usual setup of using a Brownian motion as a driving force, in this paper, the underlying system is assumed to be subject to wideband type of noise perturbations. The main thought is that Brownian motion is an idealization used in a wide range of applications, whereas the wideband noise processes is much easier to be realized in the actual applications. Although it is a good approximation to a diffusion process, the process under wideband noise becomes non-Markovian. Using weak convergence methods, we show that the limits are the desired Kolmogorov systems driven by Brownian motions.

Keywords: Wideband noise; Kolmogorovsystem; Non-Markov model; Weak convergence (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:531:y:2019:i:c:s037843711931009x

DOI: 10.1016/j.physa.2019.121746

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