基于频域小波变换的Fourier去卷积法研究

将小波变换用于对频域信号的处理,提出了用频域小波变换获得的模糊项作为线性函数的Fourier去卷积法.与其他FSD方法相比较,本文提出的方法对不同类型峰形信号如HPLC信号均具有良好的分辨效果.由于不用选择线性函数,该方法还具有通用性较强,操作简便等优点.重叠峰分辨效果好的主要原因是由于从Fourier变换得到的模与其经小波变换获得的模糊项具有相似的线性和峰宽,能较大程度与原始谱峰相符.该方法有望用于不同类型重叠峰信号的分辨.

Fourier self-deconvolution based on frequency domain wavelet transform

A new method of resolving overlapped peak,Fourier self-deconvolution(FSD)using approximation obtained from frequency domain wavelet transform as the linear function,was presented in this paper.Compared with classical FSD,the new method exhibits excellent resolution for different overlapped peak signals such as HPLC signals,and have some characteristics such as an extensive ap- plicability for any overlapped peak shape signals and a simple operation because of no selection procedure of the linear function.Its ex- cellent resolution for those different overlapped peak signals is mainly because obtained from Fourier transform of overlapped peak sig- nals and approximation obtained from wavelet transform have the similar linearity and peak width.This method has good potential in the process of different overlapped peak signals.