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脑机接口的线性和非线性方法。

Linear and nonlinear methods for brain-computer interfaces.

作者信息

Müller Klaus-Robert, Anderson Charles W, Birch Gary E

机构信息

Fraunhofer FIRST.IDA, Berlin, Germany.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2003 Jun;11(2):165-9. doi: 10.1109/TNSRE.2003.814484.

Abstract

At the recent Second International Meeting on Brain-Computer Interfaces (BCIs) held in June 2002 in Rensselaerville, NY, a formal debate was held on the pros and cons of linear and nonlinear methods in BCI research. Specific examples applying EEG data sets to linear and nonlinear methods are given and an overview of the various pros and cons of each approach is summarized. Overall, it was agreed that simplicity is generally best and, therefore, the use of linear methods is recommended wherever possible. It was also agreed that nonlinear methods in some applications can provide better results, particularly with complex and/or other very large data sets.

摘要

在2002年6月于纽约伦斯勒维尔举行的最近一次第二届脑机接口国际会议上,就脑机接口研究中线性方法和非线性方法的优缺点展开了一场正式辩论。给出了将脑电图数据集应用于线性和非线性方法的具体示例,并总结了每种方法的各种优缺点。总体而言,大家一致认为简单性通常是最好的,因此,建议尽可能使用线性方法。还达成共识,即在某些应用中非线性方法可以提供更好的结果,特别是对于复杂和/或其他非常大的数据集。

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