Global dissipativity of a class of BAM neural networks with time-varying and unbound delays

In this paper, we study the global dissipativity of a class of BAM neural networks with both time-varying and unbound delays. Based on Lyapunov functions and inequality techniques, several algebraic criteria for the global dissipativity are obtained. And the linear matrix inequality (LMI) approach is exploited to establish sufficient easy-to-test conditions which are related to the derivative of delay for the global dissipativity. Meanwhile, the estimations of the positive invariant set, globally attractive set and globally exponential attractive set are given out. Finally, two examples are presented and analyzed to demonstrate our results.

► The research highlights of paper entitled “Global dissipativity of a class of BAM neural networks with time-varying and unbound delays” are listed as follow.
► The global dissipativity of BAM neural networks is studied.
► The detail estimations for the globally exponential attractive set are obtained.
► The time delays are unbounded but not the infinite distributed delays.
► Some sufficient conditions are in linear matrix inequality form.