Channel Selection for Brain Signal Classification by Penalized Automatic Relevance Determination

被引：0

作者：

Togashi, Reo ^{[1
]}

Washizawa, Yoshikazu ^{[1
]}

机构：

[1] Univ Electrocommun, Tokyo, Japan

来源：

2015 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA) | 2015年

关键词：

COMPUTER INTERFACES; COMMUNICATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Channel selection or reduction in Brain computer interface (BCI) is important to reduce the cost and improve the generalized accuracy. A channel selection method using group automatic relevance determination (GARD) for P300 based BCI has been reported. In this paper, we apply the penalized ARD (PARD) which is an extension of ARD, and compare with GARD in our auditory BCI. Experimental results show that PARD provides more sparse solution than GARD while PARD shows almost the same classification accuracy as GARD.

引用

页码：1023 / 1027

页数：5

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