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Yanqiu Che

Showing results (11-20 of 31) with videos related to

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 8, 2009
Robust complete synchronization of electrical coupling neurons under uncertain heterogeneous disturbances using adaptive internal modelXile Wei, Jiang Wang, Yanqiu Che, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|November 13, 2019
Application of Reinforcement Learning to Deep Brain Stimulation in a Computational Model of Parkinson's DiseaseMeili Lu, Xile Wei, Yanqiu Che, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|March 14, 2020
Comments and Corrections Corrections to "Application of Reinforcement Learning to Deep Brain Stimulation in a Computational Model of Parkinson's Disease"Meili Lu, Xile Wei, Yanqiu Che, et al.
Chaos (Woodbury, N.Y.)|July 5, 2012
Parameter estimation of the FitzHugh-Nagumo model using noisy measurements for membrane potentialYanqiu Che, Li-Hui Geng, Chunxiao Han, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 28, 2019
Training Spiking Neural Networks for Cognitive Tasks: A Versatile Framework Compatible With Various Temporal CodesChaofei Hong, Xile Wei, Jiang Wang, et al.
Entropy (Basel, Switzerland)|January 8, 2025
Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear ModelQing Qin, Kaiyue Zhang, Yanqiu Che, et al.
Chaos (Woodbury, N.Y.)|February 2, 2015
Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled populationXile Wei, Danhong Zhang, Meili Lu, et al.
Cognitive Neurodynamics|November 18, 2024
Automatic detection of Alzheimer's disease from EEG signals using an improved AFS-GA hybrid algorithmRuofan Wang, Qiguang He, Lianshuan Shi, et al.
Frontiers in Neuroscience|August 24, 2023
A deep learning framework for identifying Alzheimer's disease using fMRI-based brain networkRuofan Wang, Qiguang He, Chunxiao Han, et al.
Frontiers in Computational Neuroscience|May 25, 2026
Feature fusion and WOA-GWO optimization for Alzheimer's disease detection with sparse EEG channelsRuofan Wang, Jitong Wang, Jiaxuan Cai, et al.
Pageof 4

Showing results (11-20 of 31) with videos related to

Sort By:
Pageof 4
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 8, 2009
Robust complete synchronization of electrical coupling neurons under uncertain heterogeneous disturbances using adaptive internal modelXile Wei, Jiang Wang, Yanqiu Che, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|November 13, 2019
Application of Reinforcement Learning to Deep Brain Stimulation in a Computational Model of Parkinson's DiseaseMeili Lu, Xile Wei, Yanqiu Che, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|March 14, 2020
Comments and Corrections Corrections to "Application of Reinforcement Learning to Deep Brain Stimulation in a Computational Model of Parkinson's Disease"Meili Lu, Xile Wei, Yanqiu Che, et al.
Chaos (Woodbury, N.Y.)|July 5, 2012
Parameter estimation of the FitzHugh-Nagumo model using noisy measurements for membrane potentialYanqiu Che, Li-Hui Geng, Chunxiao Han, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 28, 2019
Training Spiking Neural Networks for Cognitive Tasks: A Versatile Framework Compatible With Various Temporal CodesChaofei Hong, Xile Wei, Jiang Wang, et al.
Entropy (Basel, Switzerland)|January 8, 2025
Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear ModelQing Qin, Kaiyue Zhang, Yanqiu Che, et al.
Chaos (Woodbury, N.Y.)|February 2, 2015
Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled populationXile Wei, Danhong Zhang, Meili Lu, et al.
Cognitive Neurodynamics|November 18, 2024
Automatic detection of Alzheimer's disease from EEG signals using an improved AFS-GA hybrid algorithmRuofan Wang, Qiguang He, Lianshuan Shi, et al.
Frontiers in Neuroscience|August 24, 2023
A deep learning framework for identifying Alzheimer's disease using fMRI-based brain networkRuofan Wang, Qiguang He, Chunxiao Han, et al.
Frontiers in Computational Neuroscience|May 25, 2026
Feature fusion and WOA-GWO optimization for Alzheimer's disease detection with sparse EEG channelsRuofan Wang, Jitong Wang, Jiaxuan Cai, et al.
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