School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan, 430073, China.
Australian AI Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, NSW 2007, Australia.
Neural Netw. 2022 Jul;151:143-155. doi: 10.1016/j.neunet.2022.03.032. Epub 2022 Apr 4.
This paper mainly focuses on the lag H synchronization problem of coupled neural networks with multiple state or delayed state couplings. On one hand, by exploiting state feedback controller and Lyapunov functional, a criterion of lag H synchronization for coupled neural networks with multiple state couplings (CNNMSCs) is insured, and lag H synchronization problem in CNNMSCs is also coped with based on the adaptive state feedback controller. On the other hand, we explore the lag H synchronization for coupled neural networks with multiple delayed state couplings (CNNMDSCs) by utilizing similar control strategies. At last, two numerical examples are presented to verify the effectiveness and correctness of lag H synchronization for CNNMSCs and CNNMDSCs.
本文主要研究了具有多重状态或时滞状态耦合的耦合神经网络的滞后 H 同步问题。一方面，通过利用状态反馈控制器和李雅普诺夫函数，给出了具有多重状态耦合的耦合神经网络（CNNMSCs）滞后 H 同步的一个准则，并基于自适应状态反馈控制器解决了 CNNMSCs 的滞后 H 同步问题。另一方面，我们利用类似的控制策略探讨了具有多重时滞状态耦合的耦合神经网络（CNNMDSCs）的滞后 H 同步问题。最后，通过两个数值例子验证了 CNNMSCs 和 CNNMDSCs 的滞后 H 同步的有效性和正确性。
