DELAY-DEPENDENT STABILITY CRITERION FOR BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH INTERVAL TIME-VARYING DELAYS

摘要

In the letter, the global asymptotic stability of bidirectional associative memory (BAM) neural networks with delays is investigated. The delay is assumed to be time-varying and belongs to a given interval. A novel stability criterion for the stability 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. Two numerical examples are illustrated to show the effectiveness of our new result.