ABSTRACT As an emerging field, the G-Itô stochastic calculus plays an important role in describing the model uncertainty. Many interesting works have been done on stochastic differential equations driven by G-Brownian motion (G-SDEs). Among the theories and applications of G-SDEs, the stability is the vital important one. In this paper, we investigate the stabilisation for G-SDEs based on G-Lyapunov function and aperiodically adaptive intermittent controller. As an application, the sufficient conditions are established for the stabilisation of stochastic Cohen–Grossberg neural networks driven by G-Brownian motion (G-SCGNNs). Finally, an example is provided to illustrate the obtained results.

中文翻译：

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G-布朗运动驱动的SDEs通过非周期性间歇控制的稳定

摘要 作为一个新兴领域，G-Itô 随机微积分在描述模型不确定性方面发挥着重要作用。关于由 G-布朗运动 (G-SDE) 驱动的随机微分方程已经完成了许多有趣的工作。在G-SDEs的理论和应用中，稳定性是至关重要的。在本文中，我们研究了基于 G-Lyapunov 函数和非周期性自适应间歇控制器的 G-SDE 的稳定性。作为应用，建立了由 G-布朗运动（G-SCGNNs）驱动的随机 Cohen-Grossberg 神经网络稳定的充分条件。最后，提供了一个例子来说明得到的结果。