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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。
The wavelet transform is used to process the signal in the frequency domain, and a Fourier deconvolution method is proposed to use the fuzzy term obtained from the wavelet transform in the frequency domain as a linear function. Compared with other FSD methods, the proposed method has good discrimination effects on different types of peak signals such as HPLC signals. Because there is no choice of linear function, the method also has the advantages of strong universality, easy operation and so on. The main reason for the good effect of overlapping peaks is that the modulus obtained from the Fourier transform has a similar linearity and peak width to the fuzzy term obtained by the wavelet transform and can largely match the original peak. This method is expected to be used to distinguish different types of overlapping peak signals.