Anti-periodic solutions for BAM-type Cohen-Grossberg neural networks with time delays

Exponential stability of periodic solutions for inertial Cohen-Grossberg-type BAM neural networks with time delays

Abstract: The paper is concerned with the existence and global exponential stability of periodic solutions for inertial Cohen-Grossberg-type BAM neural networks with time delays. With variable transformation the system is transformed to first order differential equations. Some new sufficient conditions ensuring the existence and global exponential stability of periodic solutions for the system ...

Periodic Solutions of Cohen-Grossberg-Type BAM Neural Networks with Time-Varying Delays

Sufficient conditions to guarantee the existence and global exponential stability of periodic solutions of a CohenGrossberg-type BAM neural network are established by suitable mathematical transformation.

Periodic Solutions of a Cohen-Grossberg-Type BAM Neural Networks with Distributed Delays and Impulses

A class of Cohen-Grossberg-type BAM neural networks with distributed delays and impulses are investigated in this paper. Sufficient conditions to guarantee the uniqueness and global exponential stability of the periodic solutions of such networks are established by using suitable Lyapunov function, the properties of M-matrix, and some suitable mathematical transformation. The results in this pa...

Anti-periodic solutions for BAM neural networks with time delays

Mean square stability of periodic solution for stochastic Cohen-Grossberg-type BAM neural networks with delays

Abstract: In this paper, the mean square exponential stability of the periodic solution of stochastic CohenGrossberg-Type BAM neural networks with delays are investigated. By constructing suitable Lyapunov function, applying Itô formula, integral mean-value theorem and Poincaré mapping, we give several sufficient conditions to guarantee the mean square exponential stability of the periodic solu...