Stability for neutral-type integro-differential neural networks with random switches in noise and delay
Computational Methods for Differential Equations, cilt.11, sa.1, ss.65-80, 2023 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 11 Sayı: 1
- Basım Tarihi: 2023
- Doi Numarası: 10.22034/cmde.2022.49283.2056
- Dergi Adı: Computational Methods for Differential Equations
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, zbMATH, Directory of Open Access Journals
- Sayfa Sayıları: ss.65-80
- Anahtar Kelimeler: Gaussian noise, General decay stability, Levy noise, Markovian jumps systems, Neural networks, Neutral-type systems, Time-varying delays
- Van Yüzüncü Yıl Üniversitesi Adresli: Evet
Özet
This paper focuses on existence, uniqueness, and stability analysis of solutions for a new kind of delayed integro- differential neural networks with Markovian switches in delays and noises. The studied system combines many types of integro-differential neural network treatises in the literature. After having presented the studied system, the existence and uniqueness of solutions are shown under Lipschitz condition. By using the Lyapunov-Krasovskii functional, some stochastic analysis techniques and the M-matrix approach, stochastic stability, and general decay stability are established. Finally, a numerical example is given to validate the main established theoretical results.