156
Views
4
CrossRef citations to date
0
Altmetric
Articles

Weak convergence of attractors of reaction–diffusion systems with randomly oscillating coefficients

, ORCID Icon & ORCID Icon
Pages 256-271 | Received 25 Sep 2017, Accepted 31 Oct 2017, Published online: 14 Nov 2017
 

ABSTRACT

We consider reaction–diffusion systems with random rapidly oscillating coefficient. We do not assume any Lipschitz condition for the nonlinear function in the system, so, the uniqueness theorem for the corresponding initial-value problem may not hold for the considered reaction–diffusion system. Under the assumption that the random function is ergodic and statistically homogeneous in space variables we prove that the trajectory attractors of these systems tend in a weak sense to the trajectory attractors of the homogenized reaction–diffusion systems whose coefficient is the average of the corresponding term of the original systems.

AMS SUBJECT CLASSIFICATIONS:

Notes

No potential conflict of interest was reported by the authors.

To the blessed memory of V. V. Zhikov.

1 The image of the attractor of evolutionary equation was taken from the internet https://fr.wikipedia.org/wiki/Attracteur.

Additional information

Funding

Work of GAC and VVC is partially supported by the Russian Foundation of Basic Researches [projects 18-01-00046], [17-01-00515]. Work of KAB is supported in part by the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan (CS MES RK) by [grant number AP05131707].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,361.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.