Existence and Global Exponential Stability of Periodic Solutions for General Neural Networks with Time-Varying Delays

Existence and Global Exponential Stability of Periodic Solutions for General Neural Networks with Time-Varying Delays

By using the coincidence degree theorem and differential inequality techniques, sufficient conditions are obtained for the existence and global exponential stability of periodic solutions for general neural networks with time-varying including bounded and unbounded delays. Some known results are improved and some new results are obtained. An example is employed to illustrate our feasible results.

Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays

Existence and Global Exponential Stability of Periodic Solution for BAM Neural Networks with Mixed Time-Varying Delays

In this paper, the problem on the existence and stability of periodic solutions is investigated for bidirectional associative memory neural networks with periodic coefficients and time-varying delays and distributed delays. Under the generalization of dropping the boundedness and monotonicity of the activation functions as well as the differentiability of the time-varying delays, several suffic...

Existence and Stability of Periodic Solutions to Time-varying Cell Neural Networks with Delays

This paper aims to study the existence and global stability of the periodic solutions to time-varying cell neural networks (CNN) with delays. By employing the Lyapunov function and inequality analysis method, the solution to this kind of delay CNN is proved to be bounded and therefore the existence criteria for its periodic solution is established. Moreover, by using Razumikhin technique, the g...

Existence and exponential stability of almost periodic solutions for CNNs with time-varying leakage delays