数学
随机微分方程
大偏差理论
有界函数
布朗运动
弱收敛
极限(数学)
领域(数学分析)
乘法函数
数学分析
应用数学
趋同(经济学)
偏微分方程
代表(政治)
随机偏微分方程
分数布朗运动
统计
计算机安全
政治
计算机科学
政治学
法学
经济
资产(计算机安全)
经济增长
作者
Gregory Amali Paul Rose,M. Suvinthra,K. Balachandran
标识
DOI:10.1142/s021949372250023x
摘要
This paper aims to establish the central limit theorem and moderate deviation principle for the stochastic Kuramoto–Sivashinsky equation driven by multiplicative noise on a bounded domain. The moderate deviation principle is investigated using the weak convergence approach based on a variational representation for expected values of positive functionals of the Brownian motion. The approach relies on proving basic qualitative properties of controlled versions of the original stochastic partial differential equation which is under consideration.
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