期刊
JOURNAL OF NEURAL ENGINEERING
卷 1, 期 4, 页码 212-217出版社
IOP PUBLISHING LTD
DOI: 10.1088/1741-2560/1/4/004
关键词
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High rate classification of imagery tasks is still one of the hot topics among the brain computer interface (BCI) groups. In order to improve this rate, a new approach based on fractal dimension as feature and Adaboost as classifier is presented for five subjects in this paper. To have a comparison, features such as band power, Hjorth parameters along with LDA classifier have been taken into account. Fractal dimension as a feature with Adaboost and LDA can be considered as alternative combinations for BCI applications.
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