EXPONENTIAL STABILITY OF BAM-TYPE NEURAL NETWORKS WITH CONFORMABLE DERIVATIVE
PROCEEDINGS OF THE INSTITUTE OF MATHEMATICS AND MECHANICS, cilt.49, sa.1, ss.78-94, 2023 (ESCI)
- 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.