EXPONENTIAL STABILITY OF BAM-TYPE NEURAL NETWORKS WITH CONFORMABLE DERIVATIVE

Kutahyalioglu A., Karakoç F.

PROCEEDINGS OF THE INSTITUTE OF MATHEMATICS AND MECHANICS, cilt.49, sa.1, ss.78-94, 2023 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49 Sayı: 1
  • Basım Tarihi: 2023
  • Doi Numarası: 10.30546/2409-4994.2023.49.1.78
  • Dergi Adı: PROCEEDINGS OF THE INSTITUTE OF MATHEMATICS AND MECHANICS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
  • Sayfa Sayıları: ss.78-94
  • Anahtar Kelimeler: Exponential stability, BAM neural networks, conformable derivative, Lyapunov function, PERIODIC-SOLUTIONS, TIME
  • Ankara Üniversitesi Adresli: Evet

Özet

This paper investigates the fractional exponential stability of bidirectional associative memory (BAM) neural networks with con-formable derivative. Applying the contraction mapping theorem exis-tence and uniqueness of the equilibrium is studied. Furthermore, an appropriate Lyapunov function is stated to get exponential stability. Numerical examples are given to illustrate the obtained results.