NOVEL STABILITY CONDITIONS FOR INTERVAL DELAYED NEURAL NETWORKS WITH MULTIPLE TIME-VARYING DELAYS

In this paper, the global exponential stability and global asymptotic stability for a class of interval delayed neural networks (IDNNs) with multiple time-varying delays are considered. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of IDNNs via linear matrix inequality (LMI) approach. Some numerical examples are illustrated to show the effectiveness of our results. From the illustrative examples, significant improvement over the recent results can be demonstrated.

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