| 基于脑电的脑-机接口:关键技术和应用前景 |
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| 引用本文： | 尧德中,刘铁军,雷旭,杨平,徐鹏,张杨松.基于脑电的脑-机接口:关键技术和应用前景[J].电子科技大学学报(社会科学版),2009(5). |
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| 作者姓名： | 尧德中 刘铁军 雷旭 杨平 徐鹏 张杨松 |
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| 作者单位： | 神经信息教育部重点实验室;电子科技大学生命科学与技术学院; |
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| 基金项目： | 国家自然科学基金(60736029); 国家863计划(2009AA02Z301) |
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| 摘 要： | 介绍了运动想像脑-机接口技术中的几项核心技术,即在信息特征提取阶段采用的共空间模式和判决空间模式滤波方法、在模式识别阶段采用的大概率测试样本扩充训练集合的贝叶斯线性判决分析方法、直推式支持向量机方法、基于流形学习的拉普拉斯支持向量机方法和基于分层贝叶斯模型的方法。介绍了在线系统设计中的放大器设计和空闲态检测,展望了未来的发展方向。
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| 关 键 词： | 脑机接口 脑电 特征提取 在线系统 模式识别 |
Electroencephalogram Based Brain-Computer Interface: Key Techniques and Application Prospect |
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| YAO De-zhong,LIU Tie-jun,LEI Xu,YANG Ping,XU Peng, ZHANG Yang-song.Electroencephalogram Based Brain-Computer Interface: Key Techniques and Application Prospect[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),2009(5). |
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| Authors: | YAO De-zhong LIU Tie-jun LEI Xu YANG Ping XU Peng ZHANG Yang-song |
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| Institution: | YAO De-zhong,LIU Tie-jun,LEI Xu,YANG Ping,XU Peng,, ZHANG Yang-song (Key Laboratory for NeuroInformation of Ministry of Education,School of Life Science , Technology,University of Electronic Science , Technology of China Chengdu 610054) |
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| Abstract: | Several key techniques of brain computer-interface based on motor imagery are introduced.For the feature extraction,emphasized are the common spatial patterns(CSP) and discriminative spatial patterns(DSP) filters;for the pattern recognition,stressed are the Bayesian linear discriminant analysis(BLDA) employed large probabilistic test samples to expand the training set,the transductive support vector machines(TSVM),the manifold-based Laplacian support vector machine(LapSvm),and the hierarchical Bayesian line... |
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| Keywords: | brain-computer interface electroencephalogram feature extraction on-line learning pattern recognition |
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