State Bounding of Memristive Cohen-Grossberg Neural Networks with Mixed Delays

This paper concerns the state bounding problem for a class of memristive Cohen–Grossberg neural networks with mixed delays and bounded disturbances. A delay-dependent sufficient condition, which is presented in terms of system parameters and contains several simple inequalities, is first given to guarantee that the state trajectories remain inside or converge exponentially into a polytope. Furthermore, based on the state bounding results, reachable set estimation and global exponential stability criterion are obtained. Finally, a numerical simulation illustrates the effectiveness of the obtained theoretical results.