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2020 Existence and exponential stability of anti-periodic solution for fuzzy BAM neural networks with inertial terms and time-varying delays
Yongkun Li, Jiali Qin
Topol. Methods Nonlinear Anal. 55(2): 403-428 (2020). DOI: 10.12775/TMNA.2020.005

Abstract

In this paper, the existence and exponential stability of anti-periodic solutions for fuzzy BAM neural networks with inertial terms and time-varying delays is investigated. Firstly, some sufficient conditions ensuring the existence of anti-periodic solutions of the system are obtained by employing a new continuation theorem of coincidence degree theory. Secondly, by constructing an appropriate Lyapunov function, some sufficient conditions are derived to guarantee the global exponential stability of anti-periodic solutions of the system. Our results of this paper are completely new. Finally, two numerical examples are given to show the effectiveness of the obtained results.

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Yongkun Li. Jiali Qin. "Existence and exponential stability of anti-periodic solution for fuzzy BAM neural networks with inertial terms and time-varying delays." Topol. Methods Nonlinear Anal. 55 (2) 403 - 428, 2020. https://doi.org/10.12775/TMNA.2020.005

Information

Published: 2020
First available in Project Euclid: 11 June 2020

zbMATH: 07243978
MathSciNet: MR4131159
Digital Object Identifier: 10.12775/TMNA.2020.005

Rights: Copyright © 2020 Juliusz P. Schauder Centre for Nonlinear Studies

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Vol.55 • No. 2 • 2020
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