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    題名: Robust synchronization of reaction–diffusion memristive neural networks with parameter uncertainties and general couplings
    作者: 曾睿彬
    Tseng, Jui-Pin
    貢獻者: 應數系
    關鍵詞: Robust synchronization;Reaction-diffusion;Delayed memristive neural network;Parameter uncertainty;Nonlinear coupling
    日期: 2025-09
    上傳時間: 2025-06-13 09:27:18 (UTC+8)
    摘要: This study investigates the robust synchronization of coupled reaction–diffusion memristive neural networks with parameter uncertainties, internal time delays, and general coupling configurations. The proposed synchronization approach relaxes restrictive assumptions on coupling structures and parameter consistency, accommodating systems with both excitatory and inhibitory connections, parameter uncertainties, and nonlinear coupling functions, which are common in real-world applications yet rarely addressed in the literature. Using a novel convergence result for a class of differential inequalities, we establish a robust synchronization criterion that is both theoretically rigorous and practically verifiable. Illustrative examples validate the effectiveness of the proposed method, demonstrating its ability to address synchronization problems in models that existing methods cannot handle. This work advances synchronization theory for memristive neural networks, extending its applicability to a broader range of systems.
    關聯: Neural Networks, Vol.189, 107509
    資料類型: article
    DOI 連結: https://doi.org/10.1016/j.neunet.2025.107509
    DOI: 10.1016/j.neunet.2025.107509
    顯示於類別:[應用數學系] 期刊論文

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