Global Robust Exponential Dissipativity of Uncertain Second-Order BAM Neural Networks With Mixed Time-Varying Delays

This article focuses on the global robust exponential dissipativity (GRED) of uncertain second-order BAM neural networks with mixed time-varying delays. First, a new differential inequality for the concerned second-order system is established. Second, by constructing some new Lyapunov-Krasovskii functionals (LKFs) and applying this new inequality and some other inequalities, some new GRED criteria in the form of linear matrix inequalities are presented. The global exponential attractive sets are also provided simultaneously. Different from the existing reduced-order methods, this article considers some new LKFs to directly analyze the dynamics of the addressed system via a nonreduced-order strategy. Finally, the correctness of the theoretical results is verified by simulation experiments.

Automated summary

This article focuses on the global robust exponential dissipativity (GRED) of uncertain second-order BAM neural networks with mixed time-varying delays. New differential inequalities and Lyapunov-Krasovskii functionals are established to present new GRED criteria in the form of linear matrix inequalities. The correctness of the theoretical results is verified through simulation experiments.