On improved delay-dependent criterion for global stability of bidirectional associative memory neural networks with time-varying delays

In the paper, the global robust asymptotic stability of bidirectional associative memory (BAM) neural networks with time-varying delays and uncertainties is investigated. A novel stability criterion is presented based on the Lyapunov method. The criterion is represented in terms of linear matrix inequality (LMI), which can be solved easily by various optimization algorithms. A numerical example is illustrated to show the effectiveness of our new result.