Large deviation principle for the stationary solutions of stochastic functional differential equations with infinite delay

Fuente: arXiv
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Autori principali: Liu, Yong, Tang, Bin
Natura: Preprint
Pubblicazione: 2025
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_version_ 1866909044549091328
author Liu, Yong
Tang, Bin
author_facet Liu, Yong
Tang, Bin
contents We investigate the large deviation principle (LDP) of the stationary solutions of stochastic functional differential equations (SFDEs) with infinite delay under small random perturbation. First, we demonstrate the existence and uniqueness of the corresponding stationary solutions. Second, by the weak convergence approach, we show the uniform large deviation principle for the solution maps, and then prove the LDP for stationary solutions. Furthermore, we obtain the LDP for invariant measures of SFDEs through the LDP for stationary solutions and the contraction principle.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07325
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Large deviation principle for the stationary solutions of stochastic functional differential equations with infinite delay
Liu, Yong
Tang, Bin
Probability
60F10, 60G10, 34K50, 37A50
We investigate the large deviation principle (LDP) of the stationary solutions of stochastic functional differential equations (SFDEs) with infinite delay under small random perturbation. First, we demonstrate the existence and uniqueness of the corresponding stationary solutions. Second, by the weak convergence approach, we show the uniform large deviation principle for the solution maps, and then prove the LDP for stationary solutions. Furthermore, we obtain the LDP for invariant measures of SFDEs through the LDP for stationary solutions and the contraction principle.
title Large deviation principle for the stationary solutions of stochastic functional differential equations with infinite delay
topic Probability
60F10, 60G10, 34K50, 37A50
url https://arxiv.org/abs/2501.07325