Global exponential stability for uncertain bidirectional associative memory neural networks with multiple time‐varying delaysviaLMI approach

The global exponential stability for uncertain delayed bidirectional associative memory neural networks (DBAMNN) with multiple time‐varying delays is considered in this paper. Delay‐dependent criteria are proposed to guarantee the robust stability of DBAMNN via linear matrix inequality approach. Two classes of system uncertainties are investigated in this paper. Some numerical examples are given to illustrate the effectiveness of our results. From the numerical simulations, significant improvement over the recent results can be observed.