小波分析理论在脑电分析中的应用

小波变换是一种把时间、频率（或尺度）两域结合起来的分析方法。它具有：（１）多分辨率；（２）相对带宽恒定；（３）适当地选择基本小波，可使小波在时、频两域都具有表征信号局部特征的能力的特点，被誉为“分析信号的显微镜”。本系统以Ｗｉｎｄｏｗｓ为操作系统平台，将小波变换用于脑电信号分析，实现病历管理，１００Ｈｚ脑电信号采样，１０分钟脑电数据存储等功能，是一个在Ｗｉｎｄｏｗｓ３．１下开发的脑电分析系统。从脑电信号小波变换后的波形可以看出，各尺度信号不仅反映信号的频率信息，同时也反映信号的时间信息，意即反映此时ＥＥＧ的状态。而传统的傅里叶分析只能获得信号的整体频谱，不能反映时域信息

WAVELET ANALYSIS THEORY AND ITS APPLICATION TO EEG ANALYSIS

Wavelet transform is an analytical method which units the time domain and frequency domain. It has 3 features: (1) Multiresolution; (2) Constant relative bandwidth; (3) Wavelets has the ability to indicate signals which is localized in time or space. It is called a mathematical microscope for analyzing signals. The Windows operating system is used as the platform, the EEG signal is analyzed with the wavelet transform in the EEG process system. This system accomplishes some functions such as case history manahement, EEG signal at the rate of 100Hz, EEG data store for 10 minutes. It is an EEG signal analytical system. Classical Fourier analysis can only obtain the full signal spectrum instead of the information of time domain. Nonstationary signal such as EEG can not be described perfectly by using Fourier analysis. By means of wavelet transform, we can obtain either the information of frequency domain or the information of time domain.