Combination of the Channel Dimension Expansion and FastICA for the Recognition of BCI Motor Imagery EEG

ZHAI Ke-wen; LIU Jian-ping; SI Xin-lu

Chinese

您当前的位置：

首页 >

文章列表页 >

Combination of the Channel Dimension Expansion and FastICA for the Recognition of BCI Motor Imagery EEG

更新时间：2026-09-04

- Combination of the Channel Dimension Expansion and FastICA for the Recognition of BCI Motor Imagery EEG
- Vol. 32, Issue 11, Pages: 180-184(2015)
- 作者机构：
  
  1. 1 武警工程大学信息工程系,陕西,西安,710086
  2. 2 西安机电信息技术研究所,陕西,西安,710065
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015
- 稿件说明：
移动端阅览
翟克文, 刘建平, 司昕路. 通道扩维与FastICA算法相融合用于BCI运动想象脑电信号识别[J]. 微电子学与计算机, 2015, 32(11): 180-184.

ZHAI Ke-wen, LIU Jian-ping, SI Xin-lu. Combination of the Channel Dimension Expansion and FastICA for the Recognition of BCI Motor Imagery EEG[J]. 2015, 32(11): 180-184.
翟克文, 刘建平, 司昕路. 通道扩维与FastICA算法相融合用于BCI运动想象脑电信号识别[J]. 微电子学与计算机, 2015, 32(11): 180-184. DOI：

ZHAI Ke-wen, LIU Jian-ping, SI Xin-lu. Combination of the Channel Dimension Expansion and FastICA for the Recognition of BCI Motor Imagery EEG[J]. 2015, 32(11): 180-184. DOI：

摘要

FastICA是独立成分分析法(ICA)中的一种快速算法

因其收敛速度快而备受关注.本文将基于负熵判据的FastICA算法应用于运动想象脑电信号的识别中

并根据ICA算法的特点设计了数据处理的实验流程.针对2003年国际BCI竞赛data set III中通道数较少的问题

提出一种通道扩维算法

在不增加采集电极数的情况下

可成倍地增加相似通道的数量

提供更丰富的脑电信息.将通道扩维与FastICA算法相融合应用于国际BCI竞赛数据的处理中

实验结果表明通道扩维算法提升了FastICA算法的分类准确率

同时FastICA算法处理信息速度较快的特点也弥补了通道扩维算法耗时较多的缺陷.

Abstract

As a fast algorithm of independent analysis (ICA)

FastICA is drawing attention due to its rapid convergence speed. Based on the application of FastICA algorithm with the criterion of neg-entropy to the recognition of motor imagery electroencephalogram (EEG)

and the characteristics of ICA

this paper designs the experimental process for data treatment. Concerning the problem of few channels in the data set III in the BCI Competition 2003

a channel dimension expansion algorithm is put forward in this paper

which can exponentially increase the number of similar channels and provide more brain electricityinformation without increasing the number of electrodeplates to be collected. In this paper

the channel dimension expansion is combined with the algorithm of FastICA to be applied to the data treatment of BCI Competition. The experiment results suggest that the channel dimension expansion algorithm can improve the classification accuracy of FastICA

and that the fast information treatment of FastICAcan make up for the time-consuming side of the channel dimension expansion algorithm.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

High gain stability high temperature operational amplifier based on reverse body bias

Simulation on the DC characteristics of double heterojunction p-GaN HEMT with AlN/GaN hybrid buffer layer

Design of ultra-low power real-time clock circuits

Microservices anomaly detection based on the correlation of monitoring metrics

Implementation and verification of a dual-chain power gating strategy for low power design

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰