Semi-supervised Temporal-spatial Filter Based on MRP for Brain-computer Interfaces

摘要：

In brain-computer interface (BCI)studies,if the number of training trails is small,the discriminative patterns of movement related potentials (MRPs)can not be appropriately extracted by temporal-spatial filter (TSF)algorithm.Thus in this paper,we proposed a semi-supervised TSF (ssTSF)algorithm which employed self-training scheme to induce the unlabelled trails with high confidences and learn the discriminative patterns of MRPs iteratively.We compared TSF and ssTSF algorithm on the data from BCI competition I.The results demonstrated the effectiveness of the ssTSF,especially for small training sets.

作者: Jun Lv Lei Wang

作者单位: College of Automation Guangdong University of Technology Guangzhou,China School of Electronic and Information Engineering South China University of Technology Guangzhou,Chin

会议类型: 国际会议

会议名称: 第八届IEEE信息与自动化国际会议(ICIC 2011)

会议地点: 深圳

会议语种:英文

页码: 519-522

在线出版日期: 2011-06-06（万方平台首次上网日期，不代表论文的发表时间）