摘要:
为有效提取脑电信号特征波,结合小波技术提出一种脑电特征波计算方法。对脑电信号进行小波分解,重构相关频段信号,提取特征波,并结合BP神经网络对其进行计算。实验结果表明,该方法有效,对3个受试者的平均识别率大于80%,适合残疾人等各种人群。
关键词:
脑电信号,
小波,
脑电密码,
BP神经网络
Abstract:
A method which used wavelet package is put forward to extract the feature of Eectroencephalogram(EEG) signals more efficiently. With the help of wavelet, the original EEG signals are decomposed and recomposed at the related frequency range, which is in order to feature extraction, and computed with BP neural network technology. Experimental result shows that the wavelet can extract the feature waves efficiently, which are obtained with more than 80 percent identification rate for three participators, person identification can be used by persons with disabilities and the general public, it has better adaptation.
Key words:
Eectroencephalogram(EEG) signal,
wavelet,
EEG password,
BP neural network Eectroencephalogram(EEG) signa,
wavelet,
EEG password,
BP neural network
中图分类号:
胡剑锋, 蒋德荣, 尹晶海, 穆振东. 基于小波分析的脑电密码计算方法[J]. 计算机工程, 2010, 36(11): 27-27-29.
HU Jian-Feng, JIANG De-Rong, YIN Jing-Hai, MU Zhen-Dong. EEG Password Computing Method Based on Wavelet Analysis[J]. Computer Engineering, 2010, 36(11): 27-27-29.