Description

• Title:
  Existence and exponential stability of anti-periodic solution for fuzzy BAM neural networks with inertial terms and time-varying delays
• Creator:
  Li, Yongkun;
  Qin, Jiali
• Description:
  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.
• Object availability:
  free access
• Rights:
  Prawa autorskie (c) 2020 Topological Methods in Nonlinear Analysis
• Date:
  2020.05.30
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion;
  Recenzowany artykuł
• Language:
  English
• Source:
  Topological Methods in Nonlinear Analysis; Vol 55, No 2 (June 2020); 403 - 428;
  1230-3429
• Publisher:
  Nicolaus Copernicus University in Toruń
• Relation: https://apcz.umk.pl/TMNA/article/view/TMNA.2020.005/25742 ;https://apcz.umk.pl/TMNA/article/view/TMNA.2020.005/25743
• Subject:
  Fuzzy BAM neural network;
  inertial term;
  continuation theorem;
  anti-periodic solution;
  34K13;
  34K36;
  92B20
• Identifier: https://apcz.umk.pl/TMNA/article/view/TMNA.2020.005
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  other