Quantized Projective Synchronization of Delayed Fractional Order Uncertain Quaternion‐Valued Neural Networks Via Direct Method
Wei Wei Zhang, Hongyong Zhao, Chunlin Sha, Jinde Cao · Mathematical Methods in the Applied Sciences · 2025
ABSTRACT This paper treats the projective synchronization (PS) in finite time for a class of delayed fractional order uncertain quaternion‐valued neural networks (DFOUQVNNs) based on event triggered quantized control (ETQC). In addition, to consider more general models, uncertainty and time delay terms are introduced into the FOQVNNs. Different from using decomposition method, the considered model is treated as a single entity. By designing a suitable Lyapunov function and applying inequality skills, sufficient criteria are derived to ensure PS in finite time of DFOUQVNNs. Furthermore, the setting time is estimated and the Zeno behavior of the system is excluded under the proposed scheme. Finally, the effectiveness of the theoretical results is validated by using a numerical example.