Boundary Sampled-Data Synchronization of Delayed Reaction-Diffusion Neural Networks
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.
Authors
- Huai‐Ning Wu (ORCID: https://orcid.org/0000-0002-4366-5147)
- Zipeng Wang (ORCID: https://orcid.org/0000-0002-6269-789X)
- Tingwen Huang (ORCID: https://orcid.org/0000-0001-9610-846X)
- Xiao‐Wei Zhang (ORCID: https://orcid.org/0000-0003-1471-0057)
- Hongyu Chen (ORCID: https://orcid.org/0000-0002-8207-1421)
- Junfei Qiao (ORCID: https://orcid.org/0000-0003-0950-7900)
Institutions
- Shenzhen University (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Shenzhen Technology University (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Transactions on Cybernetics
- Published
- 2025-09-03
- DOI
- https://doi.org/10.1109/tcyb.2025.3599201
- Citations
- 2
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Beijing Postdoctoral Science Foundation
- National Key Research and Development Program of China