College of Mathematics and Information Science, Henan University of Economics and Law, Zhengzhou, 450046, China.
School of Mathematics, and Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing, 210096, China.
Neural Netw. 2024 Dec;180:106717. doi: 10.1016/j.neunet.2024.106717. Epub 2024 Sep 11.
This study explores the bipartite secure synchronization problem of coupled quaternion-valued neural networks (QVNNs), in which variable sampled communications and random deception attacks are considered. Firstly, by employing the signed graph theory, the mathematical model of coupled QVNNs with structurally-balanced cooperative-competitive interactions is established. Secondly, by adopting non-decomposition method and constructing a suitable unitary Lyapunov functional, the bipartite secure synchronization (BSS) criteria for coupled QVNNs are obtained in the form of quaternion-valued LMIs. It is essential to mention that the structurally-balanced topology is relatively strong, hence, the coupled QVNNs with structurally-unbalanced graph are further studied. The structurally-unbalanced graph is treated as an interruption of the structurally-balanced graph, the bipartite secure quasi-synchronization (BSQS) criteria for coupled QVNNs with structurally-unbalanced graph are derived. Finally, two simulations are given to illustrate the feasibility of the suggested BSS and BSQS approaches.
本研究探讨了具有变量采样通信和随机欺骗攻击的四元数神经网络(QVNN)的双部分安全同步问题。首先,通过使用符号图理论,建立了具有结构平衡合作竞争相互作用的耦合 QVNN 的数学模型。其次,采用非分解方法和构造合适的幺正李雅普诺夫函数,得到了耦合 QVNN 的双部分安全同步(BSS)准则,其形式为四元数 LMI。需要提到的是,结构平衡拓扑相对较强,因此,进一步研究了具有结构不平衡图的耦合 QVNN。将结构不平衡图视为结构平衡图的中断,推导出具有结构不平衡图的耦合 QVNN 的双部分准同步(BSQS)准则。最后,给出了两个仿真来验证所提出的 BSS 和 BSQS 方法的可行性。