Positive Solutions and Exponential Stability of Nonlinear Time-Delay Systems in the Model of BAM-Cohen-Grossberg Neural Networks

In this paper, the problems of positivity and exponential stability a BAM-Cohen-Grossberg neural networks model with time-varying delays and nonlinear self-excitation rates are studied. By novel comparison techniques via differential-integral inequalities, the exponential convergence of state trajec...

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Bibliographic Details
Published in:Differential equations and dynamical systems 2024, Vol.32 (3), p.909-932
Main Authors: Dzung, Le Thi Hong, Van Hien, Le
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Convexity
Engineering
Linear programming
Mathematics
Mathematics and Statistics
Neural networks
Nonlinear systems
Original Research
Self excitation
Stability
Time delay systems
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Summary:In this paper, the problems of positivity and exponential stability a BAM-Cohen-Grossberg neural networks model with time-varying delays and nonlinear self-excitation rates are studied. By novel comparison techniques via differential-integral inequalities, the exponential convergence of state trajectories to a unique positive equilibrium is established by tractable linear programming conditions, which can be effectively solved by various convex optimization algorithms. Numerical simulations are given to illustrate the effectiveness of the obtained theoretical results.
ISSN:0971-3514
0974-6870
DOI:10.1007/s12591-022-00605-y