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拉曼光谱已被广泛应用,但它常含有大量干扰信息,有时严重影响了样品的光谱特征。因此在光谱分析和处理中降噪显得极为重要。针对拉曼光谱的噪声特性,提出将最小均方(LMS)自适应滤波器应用于拉曼光谱的降噪处理。将该方法应用于信噪比(SNR)低于10d B的纯R6G拉曼光谱中,LMS自适应滤波器算法能充分保留有效信号的细节和包络,并与小波变换和集合经验模态分解(EEMD)算法一一对比分析。通过SNR、均方根误差(RMSE)和相关系数(ρ)这三个评价标准充分证明LMS自适应滤波器在拉曼光谱中的降噪优势。
Raman spectroscopy has been widely used, but it often contains a lot of interference information, and sometimes severely affected the spectral characteristics of the sample. Therefore, noise reduction in spectrum analysis and processing is extremely important. In view of the noise characteristics of Raman spectrum, a minimum mean square (LMS) adaptive filter is proposed for the noise reduction of Raman spectrum. Applying this method to the pure R6G Raman spectrum with a signal-to-noise ratio (SNR) less than 10d B, the LMS adaptive filter algorithm preserves the details and envelope of the valid signal sufficiently and is in good agreement with the wavelet transform and the set empirical mode decomposition (EEMD) algorithm one by one comparative analysis. The three evaluation criteria of SNR, root mean square error (RMSE) and correlation coefficient (ρ) fully demonstrate the noise reduction advantage of LMS adaptive filter in Raman spectrum.