Stability for neutral-type integro-differential neural networks with random switches in noise and delay

Imzegouan C., Zouine A., Bouzahir H., Tunç C.

Computational Methods for Differential Equations, vol.11, no.1, pp.65-80, 2023 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 1
  • Publication Date: 2023
  • Doi Number: 10.22034/cmde.2022.49283.2056
  • Journal Name: Computational Methods for Differential Equations
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, zbMATH, Directory of Open Access Journals
  • Page Numbers: pp.65-80
  • Keywords: Gaussian noise, General decay stability, Levy noise, Markovian jumps systems, Neural networks, Neutral-type systems, Time-varying delays
  • Van Yüzüncü Yıl University Affiliated: Yes

Abstract

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.