Periodic solution for inertial neural networks with variable parameters

Periodic solution for inertial neural networks with variable parameters

We discuss periodic solution problems and asymptotic stability for inertial neural networks with D−operator and variable parameters. Based on Mawhin's continuation theorem and Lyapunov functional method, some new sufficient conditions on the existence and asymptotic stability of periodic soluti...

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Bibliographic Details
Main Authors: Lingping Zhang, Bo Du
Format: Article
Language:English
Published: AIMS Press 2021-09-01
Series:AIMS Mathematics
Subjects:
periodic solution
asymptotic stability
inertial neural networks
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2021789?viewType=HTML
Description
Summary:We discuss periodic solution problems and asymptotic stability for inertial neural networks with D−operator and variable parameters. Based on Mawhin's continuation theorem and Lyapunov functional method, some new sufficient conditions on the existence and asymptotic stability of periodic solutions are established. Finally, a numerical example verifies the effectiveness of the obtained results.
ISSN:2473-6988

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