Global dissipativity of Cohen-Grossberg neural networks with mixed delays

This paper is concerned with global dissipativity of a general class of Cohen-Grossberg neural networks with both discrete time-varying delays and distributed time-varying delays. Based on the Lyapunov method, linear matrix inequality approach and some inequality techniques, some sufficient conditions are presented for checking the global dissipativity for Cohen- Grossberg neural networks with mixed time-varying delays, and characterizing the sets of global dissipativity and global exponentially dissipativity. Finally, some numerical simulations are given to show the effectiveness and feasibility of the results.