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里曼的几何学和集体学习来解码跨会话的运动图像,脑电图信号

Lincong Pan1,2, Kun Wang1,3, Lichao Xu1

  • 1Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.

Journal of neural engineering
|November 6, 2023
PubMed
概括

基于里曼几何学的新型自适应增强和投票组合 (RAVE) 算法通过有效处理跨会话信号变化来改进运动康复的脑电脑接口 (BCI). 这种方法显著提高了表现,即使训练数据最小.

关键词:
里曼的几何学是里曼的几何学.适应性增强是适应性的增强.大脑计算机接口 (BCI)跨会期的变化率的跨会期的变化.电脑电图 (EEG) 是一种电脑电图.转移学习转移学习

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Signal Flow Graphs01:18

Signal Flow Graphs

Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...