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

Altun Y.

Nonlinear Studies, cilt.29, sa.2, ss.635-647, 2022 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 2
  • Basım Tarihi: 2022
  • Dergi Adı: Nonlinear Studies
  • Derginin Tarandığı İndeksler: Scopus, Academic Search Premier, zbMATH
  • Sayfa Sayıları: ss.635-647
  • Anahtar Kelimeler: Asymptotically stability, Fractional neutral-type neural networks, Lmi, Lyapunov-krasovskii functional, Rl derivate
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

© 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