摘要
奇异系统分析具有抑制噪声的效果 ,并且方法简单 ,计算量小。睡眠脑电的奇异系统分析表明 ,第一主成分含量明显反映了睡眠状态差异 :在清醒时最低 ,随着睡眠加深逐渐增加 ,但在REM期时介于S1期和S2期之间。这一结果基本不受个体、数据长度、嵌入维数以及延迟时间的影响。
Singular system analysis have the advantages of restrain noise, simple and calculate easily. In Singular system analysis of sleep EEG, we find the first principal component reflect clearly the difference of sleep stages: the first principal component is lowest in wake, it increase with sleep going deep, but during REM, it's level is between S1 and S2. This result not change by and large when object, the length of data, embedded dimensions and delay time change.
出处
《北京生物医学工程》
2004年第3期195-197,共3页
Beijing Biomedical Engineering
基金
国家自然科学基金 ( 60 0 710 2 3 )资助
关键词
脑电
奇异系统分析
睡眠状态
主成分
Sleep stage EEG Singular system analysis Principal component
