首页> 外文会议>Artifical neural networks in engineering conference >A preliminary investigation of selection of eeg and psychophysiological features for classifying pilot workload
【24h】

A preliminary investigation of selection of eeg and psychophysiological features for classifying pilot workload

机译:脑电站和心理生理特征选择初步调查,用于分类试验工作量

获取原文

摘要

Cardiac and respiration measures have shown limited success in classifying pilot workload. In the last few years, electroencephalography (EEG) measures have also been used to classify pilot workload (Sterman et al, 1992, and Wilson et al, 1994). Features of EEG data are currently selected by minimization of pilot workload classification error by a multilayer perceptron (MLP) classifier (Wilson et al, 1994). A set of salient features has not yet been idnetified for classifying pilot workload.
机译:心脏和呼吸措施在分类飞行员工作量方面表现出有限的成功。在过去的几年中,脑电图(EEG)措施也被用于对飞行员工作量进行分类(斯特别纳等,1992,和Wilson等,1994)。目前通过MultiDayer Perceptron(MLP)分类器(Wilson等,1994)最小化导频工作负载分类错误来选择EEG数据的功能。对于分类导频工作负载,尚未对一组显着的功能尚未确定。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号