This paper focuses on a class of delayed fractional Cohen–Grossberg neural networks with the fractional order between 1 and 2. Two kinds of criteria are developed to guarantee the finite-time stability of networks based on some analytical techniques. This method is different from those in some earlier works. Moreover, the obtained criteria are expressed as some algebraic inequalities independent of the Mittag–Leffler functions, and thus, the calculation is relatively simple in both theoretical analysis and practical applications. Finally, the feasibility and validity of obtained results are supported by the analysis of numerical simulations.

中文翻译：

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一类具有时滞的高阶分数阶Cohen-Grossberg神经网络的有限时间稳定性判据

本文关注一类分数阶介于1和2之间的时滞分数阶Cohen-Grossberg神经网络。基于一些分析技术，开发了两种准则来保证网络的有限时间稳定性。此方法与某些早期的作品不同。此外，获得的标准表示为独立于Mittag-Leffler函数的一些代数不等式，因此，在理论分析和实际应用中，计算都相对简单。最后，通过数值模拟分析，证明了所获得结果的可行性和有效性。