Existence and exponential stability of anti-periodic solution for fuzzy BAM neural networks with inertial terms and time-varying delays

Yongkun Li, Jiali Qin

DOI: http://dx.doi.org/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.

Keywords


Fuzzy BAM neural network; inertial term; continuation theorem; anti-periodic solution

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