Global asymptotic stability of a larger class of neural networks with constant time delay
PHYSICS LETTERS A, cilt.311, sa.6, ss.504-511, 2003 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 311 Sayı: 6
- Basım Tarihi: 2003
- Doi Numarası: 10.1016/s0375-9601(03)00569-3
- Dergi Adı: PHYSICS LETTERS A
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.504-511
- Anahtar Kelimeler: delayed neural networks, equilibrium analysis, Lyapunov-Krasovskii functional, global asymptotic stability, EXPONENTIAL STABILITY, ROBUST STABILITY, PERIODIC-SOLUTIONS
- İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet
Özet
This Letter presents some new sufficient conditions for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with constant time delay. It is shown that the use of a more general type of Lyapunov-Krasovskii functional enables us to establish global asymptotic stability of a larger class of delayed neural networks than those considered in some previous papers. (C) 2003 Elsevier Science B.V. All rights reserved.