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Securing bipartite synchronization of neural networks under multi-rate sampling and switching topologies

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  • Si, Xindong
  • Li, Wuquan

Abstract

In this paper, the bipartite synchronization problem of coupled neural networks with sign-switching topology under replay attacks is investigated based on multi-rate sampled-data control. First, an error system model incorporating a Laplacian matrix coupling term is constructed based on graph theory and the properties of the switching topology. Second, a pinning multi-rate sampled-data controller is designed by incorporating the multi-rate sampled-data control scheme and the characteristics of replay attacks. Then, a looped-function that remains positive definite only at sampling instants is constructed. Considering the discrete-continuous Lyapunov stability theory and inequality techniques, a mean-square bipartite synchronization criterion is derived. Finally, the effectiveness and advantages of the control scheme and the constructed Lyapunov function are verified through numerical examples and the maximum allowable sampling interval algorithm.

Suggested Citation

  • Si, Xindong & Li, Wuquan, 2026. "Securing bipartite synchronization of neural networks under multi-rate sampling and switching topologies," Chaos, Solitons & Fractals, Elsevier, vol. 207(C).
    • Handle: RePEc:eee:chsofr:v:207:y:2026:i:c:s0960077926002122
    DOI: 10.1016/j.chaos.2026.118071
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