Convergence and Approximation of Invariant Measures for Neural Field Lattice Models under Noise Perturbation-Reference-Cited by-同舟云学术

Convergence and Approximation of Invariant Measures for Neural Field Lattice Models under Noise Perturbation

Published:2024-01-24 Issue:1 Volume:23 Page:358-382
ISSN:1536-0040
Container-title:SIAM Journal on Applied Dynamical Systems
language:en
Short-container-title:SIAM J. Appl. Dyn. Syst.

Author:

Caraballo Tomas¹^ORCID,Chen Zhang²^ORCID,Li Lingyu³

Affiliation:

1. Dpto. Ecuaciones Diferenciales y Análisis Numérico, Facultad de Matemáticas, Universidad de Sevilla 41012, Spain, and Department of Mathematics, Wenzhou University, Wenzhou, Zhejiang, Province 325035, China.

2. Co-corresponding author. School of Mathematics, Shandong University, Jinan 250100, China.

3. Co-corresponding author. School of Mathematical Sciences, University of Jinan, Jinan 250022, China, and School of Mathematics, Shandong University, Jinan 250100, China.

Funder

Ministerio de Ciencia, Innovación y Universidades

National Natural Science Foundation of China

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference53 articles.

1. Globally Coupled Anosov Diffeomorphisms: Statistical Properties

2. Approximation of Invariant Measures for Regime-switching Diffusions

3. A Discrete Convolution Model¶for Phase Transitions

4. ATTRACTORS FOR STOCHASTIC LATTICE DYNAMICAL SYSTEMS

5. Attractors of non-autonomous stochastic lattice systems in weighted spaces

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