Antiperiodic Solutions to Impulsive Cohen-Grossberg Neural Networks with Delays on Time Scales

Abstract

We use the method of coincidence degree and construct suitable Lyapunov functional to investigate the existence and global exponential stability of antiperiodic solutions of impulsive Cohen-Grossberg neural networks with delays on time scales. Our results are new even if the time scale $\mathbb{T}=\mathbb{R}$ or $\mathbb{Z}$. An example is given to illustrate our feasible results.