Abstract
In this Letter, a class of fuzzy Cohen–Grossberg neural networks (FCGNNs) with time-varying delays is investigated. With removing some restrictions on the amplification functions, a new nonlinear delay differential inequality is established, which improves previously known criteria. By using the properties of M-cone and a generalization of Barbǎlat's lemma, the boundedness and asymptotic behavior for the solution of the inequality are obtained. Applying this nonlinear delay differential inequality, a series of new and useful criteria are obtained to ensure the existence of global attracting set and invariant set for FCGNNs with time-varying delays. An example is given to illustrate the effectiveness of our results.
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