Journal
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
Volume 45, Issue 16, Pages 10476-10490Publisher
WILEY
DOI: 10.1002/mma.8379
Keywords
anti-periodic solution; Banach's fixed theorem; exponential stability; inertial neural networks; time-varying delay
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This paper investigates a class of inertial neural networks with time delays. By employing the approach of differential inequality techniques coupled with Lyapunov function method, the exponential stability of almost anti-periodic solutions for the dynamical system described by the model is demonstrated. Two numerical examples are provided to illustrate the feasibility of the theoretical outcomes.
In this paper, a class of inertial neural networks with time delays is considered. By developing an approach based on differential inequality techniques coupled with Lyapunov function method, some assertions are demonstrated to guarantee the exponential stability of almost anti-periodic solutions for the dynamical system described the model. Finally, two numerical examples to illustrate the feasibility of our theoretical outcomes.
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