Global Mittag–Leffler Stabilization of Fractional-Order BAM Neural Networks with Linear State Feedback Controllers

Abstract EN

In this paper, the global Mittag–Leffler stabilization of fractional-order BAM neural networks is investigated.

First, a new lemma is proposed by using basic inequality to broaden the selection of Lyapunov function.

Second, linear state feedback control strategies are designed to induce the stability of fractional-order BAM neural networks.

Third, based on constructed Lyapunov function, generalized Gronwall-like inequality, and control strategies, several sufficient conditions for the global Mittag–Leffler stabilization of fractional-order BAM neural networks are established.

Finally, a numerical simulation is given to demonstrate the effectiveness of our theoretical results.