Exponential stability of Hopfield neural networks with conformable fractional derivative

Kutahyalioglu A., Karakoç F.

NEUROCOMPUTING, cilt.456, ss.263-267, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 456
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.neucom.2021.05.076
  • Dergi Adı: NEUROCOMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, zbMATH
  • Sayfa Sayıları: ss.263-267
  • Anahtar Kelimeler: Hopfield neural networks, Conformable fractional derivative, Exponential stability, Lyapunov function
  • Ankara Üniversitesi Adresli: Evet

Özet

A class of Hopfield neural networks with conformable fractional derivative is studied. Sufficient conditions are derived for the existence and uniqueness of the equilibrium point of the network. Moreover, by using a Lyapunov function exponential stability result is proved. (c) 2021 Elsevier B.V. All rights reserved.