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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 13-六月-2025 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 https://doi.org/10.1016/j.neunet.2025.107509
dc.contributor 應數系
dc.creator (作者) 曾睿彬
dc.creator (作者) Tseng, Jui-Pin
dc.date (日期) 2025-09
dc.date.accessioned 13-六月-2025 09:27:18 (UTC+8)-
dc.date.available 13-六月-2025 09:27:18 (UTC+8)-
dc.date.issued (上傳時間) 13-六月-2025 09:27:18 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/157343-
dc.description.abstract (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.
dc.format.extent 108 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Neural Networks, Vol.189, 107509
dc.subject (關鍵詞) Robust synchronization; Reaction-diffusion; Delayed memristive neural network; Parameter uncertainty; Nonlinear coupling
dc.title (題名) Robust synchronization of reaction–diffusion memristive neural networks with parameter uncertainties and general couplings
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.neunet.2025.107509
dc.doi.uri (DOI) https://doi.org/10.1016/j.neunet.2025.107509