In this paper, we introduce the notion of stability of sets for reaction-diffusion Cohen–Grossberg neural networks with time-varying delays. The Lyapunov–Razumikhin technique and a comparison principle are adapted to prove the new stability criteria. In addition, the obtained results are extended to the uncertain case, and the robust stability notion is also investigated. Examples are considered to demonstrate the effectiveness of our results.

中文翻译：

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反应扩散Cohen-Grossberg时滞神经网络集合的稳定性

在本文中，我们介绍了具有时变时滞的反应扩散Cohen-Grossberg神经网络的集合稳定性的概念。Lyapunov–Razumikhin技术和比较原理适用于证明新的稳定性标准。此外，将所得结果扩展到不确定情况，并研究了鲁棒稳定性概念。示例被认为是证明我们的结果的有效性。