Dissipativity and quasi-synchronization for neural networks with discontinuous activations and parameter mismatches

In this paper, global dissipativity and quasi-synchronization issues are investigated for the delayed neural networks with discontinuous activation functions. Under the framework of Filippov solutions, the existence and dissipativity of solutions can be guaranteed by the matrix measure approach and the new obtained generalized Halanay inequalities. Then, for the discontinuous master–response systems with parameter mismatches, quasi-synchronization criteria are obtained by using feedback control. Furthermore, when the proper approximate functions are selected, the complete synchronization can be discussed as a special case that two systems are identical. Numerical simulations on the chaotic systems are presented to demonstrate the effectiveness of the theoretical results.

► We investigate the quasi-synchronization of discontinuous neural networks. ► The global dissipativity for the discontinuous system can be guaranteed. ► The quasi-synchronization of two non-identical systems can further be ensured. ► We give some numerical examples to verify the theoretical results.