Boundary Sampled-Data Synchronization of Delayed Reaction-Diffusion Neural Networks

作者：Zipeng Wang, Hongyu Chen, Junfei Qiao, Huai‐Ning Wu, Tingwen Huang, Xiao‐Wei Zhang · 发表于：IEEE Transactions on Cybernetics · 年份：2025 · DOI：10.1109/tcyb.2025.3599201 · 被引用次数：3 · 研究领域：Neural Networks and Applications

We study the synchronization of delayed reaction-diffusion neural networks (RDNNs) with Neumann boundary conditions, considering both distributed and discrete delays. Particularly, boundary sampled-data (SD) control is proposed to synchronize delayed RDNNs. In the proposed synchronization strategy, boundary SD control is based on boundary and distributed SD measurements. Based on the Lyapunov stability theory and inequality techniques, some synchronization criteria via the boundary SD control are proposed for delayed RDNNs. The boundary SD control gains are obtained by solving the conditions with linear matrix inequalities. Finally, a numerical example is presented to demonstrate the feasibility and effectiveness of the proposed method.