Exponential stability of Hopfield neural networks of neutral type with multiple time-varying delays

This paper investigates the problem for exponential stability of Hopfield neural networks of neutral type with multiple time-varying delays. Different from the existing results, the states of the neurons involve multiple time-varying delays and time derivative of states of neurons also include multiple time-varying delays. The exponential stability of such neutral-type system has not been received enough attention since it is not easy to construct a suitable Lyapunov-Krasovskii functional to analyze the exponential stability of this type of neural system. Novel sufficient conditions of the exponential stability are established by using Lyapunov method and inequality techniques. Compared with some references, the mathematical expression of the neutral-type system is more general and the established algebraic conditions are less conservative. Three examples are given to demonstrate the effectiveness of the theoretical results and compare the established stability conditions to the previous results.

Automated summary

This paper investigates the problem of exponential stability of Hopfield neural networks of neutral type with multiple time-varying delays. Novel sufficient conditions for the exponential stability are established using Lyapunov method and inequality techniques. The mathematical expression of the neutral-type system is more general and the established algebraic conditions are less conservative compared to some references.