Wei Ruoyu, Cao Jinde
School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China.
School of Mathematics, Southeast University, Nanjing 210096, China.
Math Biosci Eng. 2022 Sep 1;19(12):12814-12832. doi: 10.3934/mbe.2022598.
In this paper, we investigate the prespecified-time bipartite synchronization (PTBS) of coupled reaction-diffusion memristive neural networks (CRDMNNs) with both competitive and cooperative interactions. Two types of bipartite synchronization are considered: leaderless PTBS and leader-following PTBS. With the help of a structural balance condition, the criteria for PTBS for CRDMNNs are derived by designing suitable Lyapunov functionals and novel control protocols. Different from the traditional finite-time or fixed-time synchronization, the settling time obtained in this paper is independent of control gains and initial values, which can be pre-set according to the task requirements. Lastly, numerical simulations are given to verify the obtained results.
在本文中，我们研究了具有竞争和合作相互作用的耦合反应扩散忆阻神经网络（CRDMNNs）的预指定时间二分同步（PTBS）。考虑了两种类型的二分同步：无领导PTBS和跟随领导PTBS。借助结构平衡条件，通过设计合适的Lyapunov泛函和新颖的控制协议，推导了CRDMNNs的PTBS准则。与传统的有限时间或固定时间同步不同，本文获得的收敛时间与控制增益和初始值无关，可根据任务要求预先设定。最后，给出了数值模拟以验证所得结果。
