LMI based approach to asymptotically stability analysis for fractional neutral-type neural networks with Riemann Liouville derivative

Altun Y.

Nonlinear Studies, vol.29, no.2, pp.635-647, 2022 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 29 Issue: 2
  • Publication Date: 2022
  • Journal Name: Nonlinear Studies
  • Journal Indexes: Scopus, Academic Search Premier, zbMATH
  • Page Numbers: pp.635-647
  • Keywords: Asymptotically stability, Fractional neutral-type neural networks, Lmi, Lyapunov-krasovskii functional, Rl derivate
  • Van Yüzüncü Yıl University Affiliated: Yes


© CSP - Cambridge, UK; I&S - Florida, USA, 2022By this research paper, we search the asymptotically stability of fractional neutral-type neural networks with Riemann Liouville (RL) derivative. The activation functions discussed in this research are assumed to be globally Lipschitz continuous. The arguments of proposed stability requirements are based upon the linear matrix inequalities (LMIs) approach, which can be easily checked using the Lyapunov-Krasovskii functional. Finally, two simple examples and their simulations are presented to demonstrate that the obtained results are computationally flexible and effective