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Stability analysis for delayed Cohen–Grossberg Clifford‐valued neutral‐type neural networks.
- Source :
- Mathematical Methods in the Applied Sciences; 11/30/2022, Vol. 45 Issue 17, p10925-10945, 21p
- Publication Year :
- 2022
-
Abstract
- The aim of this study is to explore the global stability of Cohen–Grossberg Clifford‐valued neutral‐type neural network models with time delays. In order to achieve the aim of this paper, and to solve the non‐commutativity problem caused by Clifford numbers multiplication, the original Clifford‐valued system is first decomposed into 2mn$$ {2}^mn $$‐dimensional real‐valued systems. Some sufficient criteria for the global stability of the addressed network models are established by constructing an appropriate Lyapunov functional. The established stability conditions have not been affected by the neutral delay and time delay values. The proposed method and results of this paper are new. The feasibility of the stability criteria obtained are verified using two numerical examples. [ABSTRACT FROM AUTHOR]
- Subjects :
- ARTIFICIAL neural networks
STABILITY criterion
Subjects
Details
- Language :
- English
- ISSN :
- 01704214
- Volume :
- 45
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- Mathematical Methods in the Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 160116491
- Full Text :
- https://doi.org/10.1002/mma.8426