In this paper, novel multi-layer networks with superior couplings are proposed firstly which are established on a non-strongly connected digraph. Within the multi-layer networks, a nonlinear coupling based on white noises is introduced, which is the feature of superior couplings. We adopt aperiodically adaptive intermittent pinning control to stabilize the multi-layer networks. An concrete analysis framework about selecting the target vertex of the control is revealed. Aperiodically adaptive intermittent control is employed on the vertex systems of the first layer networks, to achieve the stabilization of the first layer networks, where the couplings of drift terms are treated as negative effects on stabilization. With the help of noise stabilization, the stabilization of the other layers networks is realized based on the stability of the first layer networks and the characteristics of the superior coupling that is based on white noises. By employing graph theory and the Lyapunov method, an almost sure exponential stabilization criterion of the multi-layer networks is acquired. As a subsequent result, the proposed theory is applied to a class of stochastic coupled oscillators with sufficient conditions being given to ensure their stability. Finally, a numerical example is provided to illustrate the feasibility of the stated theoretical results.

在本文中，首先提出了在非强连接有向图中建立的具有优良耦合的新型多层网络。在多层网络中，引入了基于白噪声的非线性耦合，这是高级耦合的特点。我们采用非周期性自适应间歇钉扎控制来稳定多层网络。揭示了选择控件目标顶点的具体分析框架。对第一层网络的顶点系统采用非周期性自适应间歇控制来实现第一层网络的稳定，其中漂移项的耦合被视为对稳定的负面影响。在噪音稳定的帮助下，其他层网络的稳定性是基于第一层网络的稳定性和基于白噪声的优耦合特性实现的。利用图论和Lyapunov方法，得到了多层网络几乎确定的指数稳定准则。作为随后的结果，所提出的理论被应用于一类随机耦合振荡器，并给出了足够的条件来确保它们的稳定性。最后，提供了一个数值例子来说明所述理论结果的可行性。作为随后的结果，所提出的理论被应用于一类随机耦合振荡器，并给出了足够的条件来确保它们的稳定性。最后，提供了一个数值例子来说明所述理论结果的可行性。作为随后的结果，所提出的理论被应用于一类随机耦合振荡器，并给出了足够的条件来确保它们的稳定性。最后，提供了一个数值例子来说明所述理论结果的可行性。