Enhanced Z-LDA for Small Sample Size Training in Brain-Computer Interface Systems

Background. Usually the training set of online brain-computer interface (BCI) experiment is small. For the small training set, it lacks enough information to deeply train the classifier, resulting in the poor classification performance during online testing. Methods. In this paper, on the basis of Z...

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Detalles Bibliográficos
Autores principales: Gao, Dongrui, Zhang, Rui, Liu, Tiejun, Li, Fali, Ma, Teng, Lv, Xulin, Li, Peiyang, Yao, Dezhong, Xu, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4621351/
https://www.ncbi.nlm.nih.gov/pubmed/26550023
http://dx.doi.org/10.1155/2015/680769

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4621351/
https://www.ncbi.nlm.nih.gov/pubmed/26550023
http://dx.doi.org/10.1155/2015/680769

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