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This algorithm combines mutual information and cross validation to construct objective function in the semi-supervised training process, and uses the constructed objective function to establish the semi-supervised model of MCICA for optimizing the parameters of SVM, and finally applies the selected optimal parameters to the data set Iva of 2005 BCI competition to verify its effectiveness. The results showed that the proposed algorithm is effective in optimizing parameters and has good robustness and generalization in solving small sample classification problems.<\/jats:p>","DOI":"10.3233\/ida-205188","type":"journal-article","created":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T18:24:19Z","timestamp":1626200659000},"page":"863-877","source":"Crossref","is-referenced-by-count":4,"title":["A new semi-supervised algorithm combined with MCICA optimizing SVM for motion imagination EEG classification"],"prefix":"10.1177","volume":"25","author":[{"given":"Xuemin","family":"Tan","sequence":"first","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]},{"given":"Chao","family":"Guo","sequence":"additional","affiliation":[{"name":"State Grid Chengdu Power Supply Company, Chengdu, Sichuan, China"}]},{"given":"Tao","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]},{"given":"Kechang","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]},{"given":"Nan","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]},{"given":"Jianying","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]},{"given":"Guoliang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China"}]}],"member":"179","reference":[{"key":"10.3233\/IDA-205188_ref1","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.neuroimage.2019.03.046","article-title":"The potential of MR-Encephalography for BCI\/Neurofeedback applications with high temporal resolution","volume":"194","author":"Luhrs","year":"2019","journal-title":"NeuroImage"},{"key":"10.3233\/IDA-205188_ref2","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.neucom.2018.04.087","article-title":"Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface","volume":"343","author":"Raza","year":"2019","journal-title":"Neurocomputing"},{"key":"10.3233\/IDA-205188_ref3","doi-asserted-by":"crossref","unstructured":"A. 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