Protocol-Based Non-Fragile State Estimation for Delayed Recurrent Neural Networks Subject to Replay Attacks

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摘要 Dear Editor, This letter focuses on the protocol-based non-fragile state estimation problem for a class of recurrent neural networks(RNNs). With the development of communication technology, the networked systems have received particular attentions. The networked system brings advantages such as easy to implement.

作者 Fan Yang Hongli Dong Yuxuan Shen Xuerong Li Dongyan Dai

机构地区 the Artificial Intelligence Energy Research Institute the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control the Sanya Offshore Oil&Gas Research Institute IEEE

出处《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期249-251,共3页 自动化学报（英文版）

基金 supported in part by the National Natural Science Foundation of China (U21A2019, 61933007) the Hainan Province Science and Technology Special Fund (ZDYF2022SHFZ105)。

关键词 NETWORK COMMUNICATION ESTIMATION

分类号 TN915.08 [电子电信—通信与信息系统] TP183 [自动化与计算机技术—控制理论与控制工程]

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Protocol-Based Non-Fragile State Estimation for Delayed Recurrent Neural Networks Subject to Replay Attacks

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