Improved Conditions for Global Asymptotic Stability of Cohen--Grossberg Neural Networks with Time-Varying Delays

The global asymptotic stability of delayed Cohen--Grossberg neural networks with impulses is investigated. Based on the new suitable Lyapunov functions and the Jacobsthal inequality, a set of novel sufficient criteria are derived for the global asymptotic stability of Cohen--Grossberg neural networks with time-varying delays and impulses. An illustrative example with its numerical simulations is given to demonstrate the effectiveness of the obtained results.