多尺度细化分析

小波变换是一个时间和频率的局域变换，因而能有效的从信号中提取信息，通过伸缩和平移等运算功能对函数或信号进行多尺度细化分析，解决了Fourier变换不能解决的许多困难问题。

Wavelet transform is a time and frequency local transformation and it can withdraw the information from the signal . Through the calculate function making the muti-scale analysis it resolves many difficult problems which Fourier transformation can 't resolve .

通过伸缩、平移等运算功能对信号进行多尺度细化分析，小波分析能有效地从信号中提取出有用信息。

By stretching , translation and other computing functions for multi-scale refinement of signal analysis , wavelet analysis can efficiently extract from the signal useful information .

它通过基函数的伸缩、平移等运算对信号进行有效多尺度细化分析，是一种非常灵活、快速和有效的高维信号处理方法，能高效从信号中提取有用信息。

It is mainly through the basis function expansion , translation and other operations to the effective signal multi-scale analysis , it is a very flexible , fast , efficient high dimensional signal processing method , can effectively extract useful information from signal .

小波变换通过伸缩和平移等运算功能对函数或信号进行多尺度细化分析，是空间和频率的局部变换，能有效地从信号中提取特征信息，能准确刻画异常点的位置和幅值的大小。

The wavelet transform is the localization analysis of time and frequency , and it can multi-scale refine the signal by calculating of flex and transition . It can extract feature information of the signal effectively , and it can find the location and the amplitude of outliers .