Exponential p-stability of second order Cohen–Grossberg neural networks with transmission delays and learning behavior

In this paper, we investigate second order Cohen–Grossberg neural networks with transmission delays and an unsupervised Hebbian-type learning behavior. By using Laypunov–Krasovskii functional, some new sufficient conditions are established for the existence and global exponential p-stability of a unique equilibrium without strict conditions imposed on self regulation functions. The obtained sufficient conditions are easy to verify and our results improve the previously known results. Finally, computer simulations are performed to illustrate exponential p-stability of equilibrium and learning dynamic behavior of neurons.