基于灰关联分析的脑电信号识别新方法

A New Method of EEG Recognition Based on Grey Correlation Analysis

脑电(EEG)信号具有随机性、非平稳性和实时性,通常受到很强的噪声干扰。文章采用灰色信号处理技术,通过建立GM(1,1)模型对提取实测EEG信号特征,提出灰关联分析的方法对建模后的数据进行分类识别,通过对两次识别结果的综合,获得了较高的正识率。

The EEG signal has the characteristic of strong randomness, nonstationarity and it is also real-time signal. Grey signal processing technology was adopted in the thesis. Features of real measured EEG signal could extracted from GM（1,1）. A new method grey correlation analysis is put forward to classifying and recognizing of different Brain function. Through integrated the two recognition results the final corrected recognition result is satisfied.