In the present paper, a quasiuniform stability result for fractional order neural networks with mixed delay is developed, based on the generalized Gronwall inequality and the Caputo fractional derivative. Sufficient conditions are derived to ensure the quasiuniform stability of the considered neural nets system. A clarification example is carried out not only to validate the authors’ theoretical results but also to show the superiority of the developed work (in terms of improved stability), compared with other similar works already published in the literature.

中文翻译：

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分数阶混合时滞神经网络的拟一致稳定性的改进。

基于广义Gronwall不等式和Caputo分数阶导数，提出了具有混合时滞的分数阶神经网络的拟一致稳定性结果。得出足够的条件以确保所考虑的神经网络系统的拟均匀稳定性。进行了一个澄清实例，不仅验证了作者的理论结果，而且还表明了与已在文献中发表的其他类似作品相比，所开发作品的优越性（就提高的稳定性而言）。